Question: A generalized equalization technique for improving image enhancement.

This paper introduces an innovative technique for enhancing the contrast of gray and color images utilizing the curvelet transform. The curvelet transform, with its superior edge representation capabilities compared to wavelets, is particularly effective for enhancing edges at multiple scales. A comparative analysis is conducted against enhancement techniques based on the wavelet transform and the Multiscale Retinex method. Through a series of examples, the evaluation is quantitatively assessed using edge detection, segmentation, and other processing applications. The results indicate that curvelet-based enhancement is particularly advantageous for noisy images, outperforming alternative methods. However, on images with minimal or no noise, the curvelet-based enhancement does not significantly surpass wavelet-based enhancement in terms of performance.

Many image restoration algorithms in recent years are based on patch processing. The core idea is to decompose the target image into fully overlapping patches, restore each of them separately, and then merge the results by a plain averaging. This concept has been demonstrated to be highly effective, leading often times to the state-of-the-art results in denoising, inpainting, deblurring, segmentation, and other applications. While the above is indeed effective, this approach has one major flaw: the prior is imposed on intermediate (patch) results, rather than on the final outcome, and this is typically manifested by visual artifacts. The expected patch log likelihood (EPLL) method by Zoran and Weiss was conceived for addressing this very problem. Their algorithm imposes the prior on the patches of the final image, which in turn leads to an iterative restoration of diminishing effect. In this paper, we propose to further extend and improve the EPLL by considering a multi-scale prior. Our algorithm imposes the very same prior on different scale patches extracted from the target image. While all the treated patches are of the same size, their footprint in the destination image varies due to subsampling. Our scheme comes to alleviate another shortcoming existing in patch-based restoration algorithms-the fact that a local (patch-based) prior is serving as a model for a global stochastic phenomenon. We motivate the use of the multi-scale EPLL by restricting ourselves to the simple Gaussian case, comparing the aforementioned algorithms and showing a clear advantage to the proposed method. We then demonstrate our algorithm in the context of image denoising, deblurring, and super-resolution, showing an improvement in performance both visually and quantitatively.

In this paper, a fast image restoration method is proposed to restore the true image from an atmospheric turbulence degraded video. A non-rigid image registration algorithm is employed to register all the frames of the video to a reference frame and determine the shift maps. The First Register Then Average And Subtract-variant (FRTAASv) method is applied to correct the geometric distortion of the reference frame. A performance comparison is presented between the proposed restoration method and the earlier Minimum Sum of Squared Differences (MSSD) image registration based FRTAASv method, in terms of processing time and accuracy. Simulation results show that the proposed method requires shorter processing time to achieve the same geometric accuracy.

A number of quality measures are evaluated for gray scale image compression. They are all bivariate, exploiting the differences between corresponding pixels in the original and degraded images. It is shown that although some numerical measures correlate well with the observers’ response for a given compression technique, they are not reliable for an evaluation across different techniques. A graphical measure called Hosaka plots, however, can be used to appropriately specify not only the amount, but also the type of degradation in reconstructed images.

A spatial gamut mapping technique is proposed to overcome the shortcomings encountered with standard pointwise gamut mapping algorithms by preserving spatially local luminance variations in the original image. It does so by first processing the image through a standard pointwise gamut mapping algorithm. The difference between the original image luminance Y and gamut mapped image luminance Y’ is calculated. A spatial filter is then applied to this difference signal, and added back to the gamut mapped signal Y’. The filtering operation can result in colors near the gamut boundary being placed outside the gamut, hence a second gamut mapping step is required to move these pixels back into the gamut. Finally, the in-gamut pixels are processed through a color correction function for the output device, and rendered to that device. Psychophysical experiments validate the superior performance of the proposed algorithm, which reduces many of the artifacts arising from standard pointwise techniques.

We present a color calibration pipeline for large camera arrays. We assume static lighting conditions for each camera, such as studio lighting or a stationary array outdoors. We also assume we can place a planar calibration target so it is visible from every camera. Our goal is uniform camera color responses, not absolute color accuracy, so we match the cameras to each other instead of to a color standard. We first iteratively adjust the color channel gains and offsets for each camera to make their responses as similar as possible. This step white balances the cameras, and for studio applications, ensures that the range of intensities in the scene are mapped to the usable output range of the cameras. Residual errors are then calibrated in post-processing. We present results calibrating an array of 100 CMOS image sensors in different physical configurations, including closely or widely spaced cameras with overlapping fields of views, and tightly packed cameras with non-overlapping fields of view. The process is entirely automatic, and the camera configuration runs in less than five minutes on the 100 camera array. CR Categories: I.4.1 [Image Processing and Computer Vision]: Digitization and Image Capture.Camera Calibration;

Taking photographs under low light conditions with a hand-held camera is problematic. A long exposure time can cause motion blur due to the camera shaking and a short exposure time gives a noisy image. We consider the new technical possibility offered by cameras that take image bursts. Each image of the burst is sharp but noisy. In this preliminary investigation, we explore a strategy to efficiently denoise multi-images or video. The proposed algorithm is a complex image processing chain involving accurate registration, video equalization, noise estimation and the use of state-of-the-art denoising methods. Yet, we show that this complex chain may become risk free thanks to a key feature: the noise model can be estimated accurately from the image burst. Preliminary tests will be presented. On the technical side, the method can already be used to estimate a non parametric camera noise model from any image burst.

How to make vision system work robustly under dynamic light conditions is still a challenging research focus in computer/robot vision community. In this paper, a novel camera parameters auto-adjusting technique based on image entropy is proposed. Firstly image entropy is defined and its relationship with camera parameters is verified by experiments. Then how to optimize the camera parameters based on image entropy is proposed to make robot vision adaptive to the different light conditions. The algorithm is tested by using the omnidirectional vision in indoor RoboCup Middle Size League environment and the perspective camera in outdoor ordinary environment, and the results show that the method is effective and color constancy to some extent can be achieved.

Image noise can present a serious problem in motion deblurring. While most state-of-the-art motion deblurring algorithms can deal with small levels of noise, in many cases such as low-light imaging, the noise is large enough in the blurred image that it cannot be handled effectively by these algorithms. In this paper, we propose a technique for jointly denoising and deblurring such images that elevates the performance of existing motion deblurring algorithms. Our method takes advantage of estimated motion blur kernels to improve denoising, by constraining the denoised image to be consistent with the estimated camera motion (i.e., no high frequency noise features that do not match the motion blur). This improved denoising then leads to higher quality blur kernel estimation and deblurring performance. The two operations are iterated in this manner to obtain results superior to suppressing noise effects through regularization in deblurring or by applying denoising as a preprocess. This is demonstrated in experiments both quantitatively and qualitatively using various image examples.

A new technique for the modelling of perceptual systems called formal modelling is developed. This technique begins with qualitative observations about the perceptual system, the so-called perceptual symmetries, to obtain through mathematical analysis certain model structures which may then be calibrated by experiment. The analysis proceeds in two different ways depending upon the choice of linear or nonlinear models. For the linear case, the analysis proceeds through the methods of unitary representation theory. It begins with a unitary group representation on the image space and produces what we have called the fundamental structure theorem. For the nonlinear case, the analysis makes essential use of infinite-dimensional manifold theory. It ber ins with a Lie group action on an image manifold and produces the fundamental structure formula. These techniques will be used to study the brightness perception mechanism of the human visual system. Several visual groups are defined and their corresponding structures for visual system models are obtained. A new transform called the Mandala transform will be deduced from a certain visual group and its implications for image processing will be discussed. Several new phenomena of brightness perception will be presented. New facts about the Mach band illusion along with new adaptation phenomena will be presented. Also a new visual illusion will be presented. A visual model based on the above techniques will be presented. It will also be shown how use of statistical estimation theory can be made in the study of contrast adaptation.

An algorithm is presented for the rapid solution of the phase of the complete wave function whose intensity in the diffraction and imaging planes of an imaging system are known. A proof is given showing that a defined error between the estimated function and the correct function must decrease as the algorithm iterates. The problem of uniqueness is discussed and results are presented demonstrating the power of the method.


Question: A generalized equalization technique for improving image enhancement.

This paper presents a new algorithm for achieving color constancy, the ability to accurately perceive an object's color under varying lighting conditions. Instead of viewing color as a surface reflectance function, the algorithm interprets it as the object's color under a standard, canonical light. This approach leads to a dual framework that identifies conditions under which color constancy is achievable. Central to this framework is the estimation of the illuminant under which the image was captured. This estimate is then utilized to select from a set of precomputed linear transformations, which are applied to the image to generate a color descriptor at each point. The illuminant estimation process relies solely on image measurements, as the color of the illuminant is inherently linked to the observed colors in the image, due to the physical limitation that surfaces cannot reflect more light than received. This principle leads to the development of two algorithms, based on different assumptions about the environment. The first algorithm, Crule, is applicable to any surface reflectance and operates by constraining the illuminant color through observed color data. The effectiveness of Crule is heavily dependent on the choice of photoreceptors; for narrowband photoreceptors, Crule performs well in a variety of settings. The second algorithm, Mwext, assumes that both surface reflectances and illuminants are from finite-dimensional spaces, enabling it to recover multiple parameters of the illuminant. However, Mwext's restrictive conditions make it less suitable as a model for human color constancy. Crule has been validated on real images of Mondriaan paintings, demonstrating its efficacy. Comparative results are also provided for Crule and the Retinex algorithm of Land, applied to a selection of real images. The empirical findings suggest that a color constancy system must adapt the gain of its receptors in a manner akin to human adaptation to achieve optimal constancy.

Image super-resolution (SR) is the process of generating a high-resolution (HR) image using one or more low-resolution (LR) inputs. Many SR methods have been proposed, but generating the small-scale structure of an SR image remains a challenging task. We hence propose a single-image SR algorithm that combines the benefits of both internal and external SR methods. First, we estimate the enhancement weights of each LR-HR image patch pair. Next, we multiply each patch by the estimated enhancement weight to generate an initial SR patch. We then employ a method to recover the missing information from the high-resolution patches and create that missing information to generate a final SR image. We then employ iterative back-projection to further enhance visual quality. The method is compared qualitatively and quantitatively with several state-of-the-art methods, and the experimental results indicate that the proposed framework provides high contrast and better visual quality, particularly for non-smooth texture areas.

In this work, a novel nonlinear filter, called tri-state median (TSM) filter, is proposed for preserving image details while effectively suppressing impulse noise. We incorporate the standard median (SM) filter and the center weighted median (CWM) filter into a noise detection framework to determine whether a pixel is corrupted, before applying filtering unconditionally. Extensive simulation results demonstrate that the proposed filter consistently outperforms other median filters by balancing the tradeoff between noise reduction and detail preservation.

Photometric methods in computer vision require calibration of the camera's radiometric response, and previous works have addressed this problem using multiple registered images captured under different camera exposure settings. In many instances, such an image set is not available, so we propose a method that performs radiometric calibration from only a single image, based on measured RGB distributions at color edges. This technique automatically selects appropriate edge information for processing, and employs a Bayesian approach to compute the calibration. Extensive experimentation has shown that accurate calibration results can be obtained using only a single input image.

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The fuzzy technique is an operator introduced in order to simulate at a mathematical level the compensatory behavior in process of decision making or subjective evaluation. The following paper introduces such operators on hand of computer vision application. In this paper a novel method based on fuzzy logic reasoning strategy is proposed for edge detection in digital images without determining the threshold value. The proposed approach begins by segmenting the images into regions using floating 3x3 binary matrix. The edge pixels are mapped to a range of values distinct from each other. The robustness of the proposed method results for different captured images are compared to those obtained with the linear Sobel operator. It is gave a permanent effect in the lines smoothness and straightness for the straight lines and good roundness for the curved lines. In the same time the corners get sharper and can be defined easily. Keywords—Fuzzy logic, Edge detection, Image processing, computer vision, Mechanical parts, Measurement.

It is important in image restoration to remove noise while preserving meaningful details such as edges and fine features. The existing edge-preserving smoothing methods may inevitably take fine detail as noise or vice versa. In this paper, we propose a new edge-preserving smoothing technique based on a modified anisotropic diffusion. The proposed method can simultaneously preserve edges and fine details while filtering out noise in the diffusion process. Since the fine detail in the neighborhood of a small image window generally have a gray-level variance larger than that of the noisy background, the proposed diffusion model incorporates both local gradient and gray-level variance to preserve edges and fine details while effectively removing noise. Experimental results have shown that the proposed anisotropic diffusion scheme can effectively smooth noisy background, yet well preserve edge and fine details in the restored image. The proposed method has the best restoration result compared with other edge-preserving methods.

A new technique for the modelling of perceptual systems called formal modelling is developed. This technique begins with qualitative observations about the perceptual system, the so-called perceptual symmetries, to obtain through mathematical analysis certain model structures which may then be calibrated by experiment. The analysis proceeds in two different ways depending upon the choice of linear or nonlinear models. For the linear case, the analysis proceeds through the methods of unitary representation theory. It begins with a unitary group representation on the image space and produces what we have called the fundamental structure theorem. For the nonlinear case, the analysis makes essential use of infinite-dimensional manifold theory. It ber ins with a Lie group action on an image manifold and produces the fundamental structure formula. These techniques will be used to study the brightness perception mechanism of the human visual system. Several visual groups are defined and their corresponding structures for visual system models are obtained. A new transform called the Mandala transform will be deduced from a certain visual group and its implications for image processing will be discussed. Several new phenomena of brightness perception will be presented. New facts about the Mach band illusion along with new adaptation phenomena will be presented. Also a new visual illusion will be presented. A visual model based on the above techniques will be presented. It will also be shown how use of statistical estimation theory can be made in the study of contrast adaptation.

This paper proposes a general weighted l2-l0 norms energy minimization model to remove mixed noise such as Gaussian-Gaussian mixture, impulse noise, and Gaussian-impulse noise from the images. The approach is built upon maximum likelihood estimation framework and sparse representations over a trained dictionary. Rather than optimizing the likelihood functional derived from a mixture distribution, we present a new weighting data fidelity function, which has the same minimizer as the original likelihood functional but is much easier to optimize. The weighting function in the model can be determined by the algorithm itself, and it plays a role of noise detection in terms of the different estimated noise parameters. By incorporating the sparse regularization of small image patches, the proposed method can efficiently remove a variety of mixed or single noise while preserving the image textures well. In addition, a modified K-SVD algorithm is designed to address the weighted rank-one approximation. The experimental results demonstrate its better performance compared with some existing methods.

This paper proposes a new approach for color transfer between two images. Our method is unique in its consideration of the scene illumination and the constraint that the mapped image must be within the color gamut of the target image. Specifically, our approach first performs a white-balance step on both images to remove color casts caused by different illuminations in the source and target image. We then align each image to share the same ‘white axis’ and perform a gradient preserving histogram matching technique along this axis to match the tone distribution between the two images. We show that this illuminant-aware strategy gives a better result than directly working with the original source and target image’s luminance channel as done by many previous methods. Afterwards, our method performs a full gamut-based mapping technique rather than processing each channel separately. This guarantees that the colors of our transferred image lie within the target gamut. Our experimental results show that this combined illuminant-aware and gamut-based strategy produces more compelling results than previous methods. We detail our approach and demonstrate its effectiveness on a number of examples.

Vectorized total variation (VTV) is very successful convex regularizer to solve various color image recovery problems. Despite the fact that color channels of natural color images are closely related, existing variants of VTV can not utilize this prior efficiently. We proposed L∞-VTV as a convex regularizer can penalize the violation of such inter-channel dependency by employing weighted L∞ (L-infty) norm. We also introduce an effective algorithm for an image denoising problem using L∞-VTV. Experimental results shows that our proposed method can outperform the conventional methods.


Question: A generalized equalization technique for improving image enhancement.

This study investigates the effectiveness of Contrast Limited Adaptive Histogram Equalization (CLAHE) in enhancing the visibility of simulated spiculations within dense mammograms, aiming to improve their detection. Simulated spiculations, indicative of potential malignancy when observed with masses, were inserted into dense mammograms, digitized at a high resolution of 50 micron pixels and 12-bit depth. The research compared original film images without CLAHE application to images processed with nine distinct combinations of clip levels and region sizes. A simulated spiculation was embedded within a dense breast tissue background, with its orientation altered for each trial. Variables in each trial encompassed spiculation orientation, contrast level, and the specific CLAHE settings applied. The experiment included 160 unique combinations of these variables, paired with 40 different background mammograms. Twenty student participants were tasked with identifying the orientation of the spiculation within the images. Statistically significant enhancements in detection accuracy were observed for spiculations processed with CLAHE, specifically when the region size was set to 32 with a clip level of 2, and when the region size was 32 with a clip level of 4. These findings suggest that the selected CLAHE settings could potentially improve the clinical detection of spiculations associated with masses in digital mammography and warrant further testing in real-world clinical settings.

One popular approach for blind deconvolution is to formulate a maximum a posteriori (MAP) problem with sparsity priors on the gradients of the latent image, and then alternatingly estimate the blur kernel and the latent image. While several successful MAP based methods have been proposed, there has been much controversy and confusion about their convergence, because sparsity priors have been shown to prefer blurry images to sharp natural images. In this paper, we revisit this problem and provide an analysis on the convergence of MAP based approaches. We first introduce a slight modification to a conventional joint energy function for blind deconvolution. The reformulated energy function yields the same alternating estimation process, but more clearly reveals how blind deconvolution works. We then show the energy function can actually favor the right solution instead of the no-blur solution under certain conditions, which explains the success of previous MAP based approaches. The reformulated energy function and our conditions for the convergence also provide a way to compare the qualities of different blur kernels, and we demonstrate its applicability to automatic blur kernel size selection, blur kernel estimation using light streaks, and defocus estimation.

This paper presents the successive mean quantization transform (SMQT). The transform reveals the organization or structure of the data and removes properties such as gain and bias. The transform is described and applied in speech processing and image processing. The SMQT is considered as an extra processing step for the mel frequency cepstral coefficients commonly used in speech recognition. In image processing the transform is applied in automatic image enhancement and dynamic range compression.

This paper proposes a simple, accurate, and robust approach to single image nonparametric blind Super-Resolution (SR). This task is formulated as a functional to be minimized with respect to both an intermediate super-resolved image and a nonparametric blur-kernel. The proposed approach includes a convolution consistency constraint which uses a non-blind learning-based SR result to better guide the estimation process. Another key component is the unnatural bi-l0-l2-norm regularization imposed on the super-resolved, sharp image and the blur-kernel, which is shown to be quite beneficial for estimating the blur-kernel accurately. The numerical optimization is implemented by coupling the splitting augmented Lagrangian and the conjugate gradient (CG). Using the pre-estimated blur-kernel, we finally reconstruct the SR image by a very simple non-blind SR method that uses a natural image prior. The proposed approach is demonstrated to achieve better performance than the recent method by Michaeli and Irani [2] in both terms of the kernel estimation accuracy and image SR quality.

Inconsistencies in the preparation of histology slides make it difficult to perform quantitative analysis on their results. In this paper we provide two mechanisms for overcoming many of the known inconsistencies in the staining process, thereby bringing slides that were processed or stored under very different conditions into a common, normalized space to enable improved quantitative analysis.

The last version of Land's (1986) retinex model for human vision's lightness and color constancy has been implemented and tested in image processing experiments. Previous research has established the mathematical foundations of Land's retinex but has not subjected his lightness theory to extensive image processing experiments. We have sought to define a practical implementation of the retinex without particular concern for its validity as a model for human lightness and color perception. We describe the trade-off between rendition and dynamic range compression that is governed by the surround space constant. Further, unlike previous results, we find that the placement of the logarithmic function is important and produces best results when placed after the surround formation. Also unlike previous results, we find the best rendition for a "canonical" gain/offset applied after the retinex operation. Various functional forms for the retinex surround are evaluated, and a Gaussian form is found to perform better than the inverse square suggested by Land. Images that violate the gray world assumptions (implicit to this retinex) are investigated to provide insight into cases where this retinex fails to produce a good rendition.

This paper proposes a two-stage adaptive method for restoration of images corrupted with impulse noise. In the first stage, the pixels which are most likely contaminated by noise are detected based on their intensity values. In the second stage, an efficient average filtering algorithm is used to remove those noisy pixels from the image. Only pixels which are determined to be noisy in the first stage are processed in the second stage. The remaining pixels of the first stage are not processed further and are just copied to their corresponding locations in the restored image. The experimental results for the proposed method demonstrate that it is faster and simpler than even median filtering, and it is very efficient for images corrupted with a wide range of impulse noise densities varying from 10% to 90%. Because of its simplicity, high speed, and low computational complexity, the proposed method can be used in realtime digital image applications, e.g., in consumer electronic products such as digital televisions and cameras.

Digital photography has made it possible to quickly and easily take a pair of images of low-light environments: one with flash to capture detail and one without flash to capture ambient illumination. We present a variety of applications that analyze and combine the strengths of such flash/no-flash image pairs. Our applications include denoising and detail transfer (to merge the ambient qualities of the no-flash image with the high-frequency flash detail), white-balancing (to change the color tone of the ambient image), continuous flash (to interactively adjust flash intensity), and red-eye removal (to repair artifacts in the flash image). We demonstrate how these applications can synthesize new images that are of higher quality than either of the originals.

A new method for shadow detection in colored urban aerial images is proposed. First, a new imaging model of shadows is presented, which indicates that hue values of shadowed image areas are larger than those of these areas non-shadowed. Based on this model, a thresholding technique is employed to detect shadowed areas. After detection, the Retinex technique is applied to shadowed and non-shadowed areas individually to compensate for shadows. Experiment results show the effectiveness of the proposed method.

This supplement provides additional details on the bilateral solver and its extensions in Sections 1–4, and a plethora of experiments and comparisons to prior work in Section 5. In Section 1 we derive the bilateral-space quadratic objective at the core of the bilateral solver. Section 2 details the bilateral-space pyramid representation used for faster initialization and preconditioning. Section 3 extends the bilateral solver to use a robust error function to cope with outliers. Section 4 improves the performance of the bilateral solver when applied to multiple output channels. Finally, in Section 5 we provide additional evaluation of the bilateral solver and extensively compare it to numerous existing and novel baseline techniques.

Two new, cost-effective thresholding algorithms for use in extracting binary images of characters from machineor hand-printed documents are described. The creation of a binary representation from an analog image requires such algorithms to determine whether a point is converted into a binary one because it falls within a character stroke or a binary zero because it does not. This thresholding is a critical step in Optical Character Recognition (OCR). I t is also essential for other Character Image Extraction (CIEJ applications, such as the processing of machine-printed or handwritten characters from carbon copy forms or bank checks, where smudges and scenic backgrounds, for example, may have to be suppressed. The first algorithm, a nonlinear, adaptive procedure, is implemented with a minimum of hardware and is intended for many CIE applications. The second is a more aggressive approach directed toward specialized, high-volume applications which justify extra complexity.


Question: A generalized equalization technique for improving image enhancement.

In the realm of digital image processing, the challenge of tone reproduction mirrors the traditional photographic task of mapping high dynamic range luminances to the limited dynamic range of prints. This problem is equally pertinent for computer graphics professionals, who must adapt digital images for display on low dynamic range screens or prints. Drawing inspiration from time-honored photographic techniques, this paper introduces a novel tone reproduction operator. Specifically, it builds upon and extends the methodologies pioneered by Ansel Adams, tailoring them for application in digital images. The resulting algorithm is straightforward yet effective, as evidenced by its successful performance across a diverse array of test images. The collaborative effort of researchers from the University of Utah and Cornell University has yielded a significant advancement in the field of photographic tone reproduction for digital images.

Erik Reinhard, Michael Stark, Peter Shirley, and Jim Ferwerda have contributed to this innovative work, demonstrating the practical application of classical photographic principles in the digital age. Their algorithm not only simplifies the process of tone reproduction but also enhances the visual quality of digital images, ensuring that they are optimally rendered for print and screen media. Through this research, the team has bridged the gap between traditional photographic wisdom and contemporary digital image processing, offering a solution that is both theoretically grounded and practically viable.

The image processing community has witnessed remarkable advances in enhancing and restoring images. Nevertheless, restoring the visual quality of underwater images remains a great challenge. End-to-end frameworks might fail to enhance the visual quality of underwater images since in several scenarios it is not feasible to provide the ground truth of the scene radiance. In this work, we propose a CNN-based approach that does not require ground truth data since it uses a set of image quality metrics to guide the restoration learning process. The experiments showed that our method improved the visual quality of underwater images preserving their edges and also performed well considering the UCIQE metric.

We present an efficient approach for high-quality non-blind deconvolution based on the use of sparse adaptive priors. Its regularization term enforces preservation of strong edges while removing noise. We model the image-prior deconvolution problem as a linear system, which is solved in the frequency domain. This clean formulation lends to a simple and efficient implementation. We demonstrate its effectiveness by performing an extensive comparison with existing non-blind deconvolution methods, and by using it to deblur photographs degraded by camera shake. Our experiments show that our solution is faster and its results tend to have higher peak signal-to-noise ratio than the state-of-the-art techniques. Thus, it provides an attractive alternative to perform high-quality non-blind deconvolution of large images, as well as to be used as the final step of blind-deconvolution algorithms.

Recognition of document images have important applications in restoring old and classical texts. The problem involves quality improvement before passing it to a properly trained OCR to get accurate recognition of the text. The image enhancement and quality improvement constitute important steps as subsequent recognition depends upon the quality of the input image. There are scenarios when high resolution images are not available and our experiments show that the OCR accuracy reduces significantly with decrease in the spatial resolution of document images. Thus the only option is to improve the resolution of such document images. The goal is to construct a high resolution image, given a single low resolution binary image, which constitutes the problem of single image super-resolution. Most of the previous work in super-resolution deal with natural images which have more information-content than the document images. Here, we use Convolution Neural Network to learn the mapping between low and the corresponding high resolution images. We experiment with different number of layers, parameter settings and non-linear functions to build a fast end-to-end framework for document image super-resolution. Our proposed model shows a very good PSNR improvement of about 4 dB on 75 dpi Tamil images, resulting in a 3% improvement of word level accuracy by the OCR. It takes less time than the recent sparse based natural image super-resolution technique, making it useful for real-time document recognition applications.

Fingerprint image enhancement is an essential preprocessing step in fingerprint recognition applications. In this paper we introduce an approach that extracts simultaneously orientation and frequency of local ridge in the fingerprint image by Gabor wavelet filter bank and use them in Gabor Filtering of image. Furthermore, we describes a robust approach to fingerprint image enhancement, which is based on integration of Gabor Filters and Directional Median Filter(DMF). In fact, Gaussian-distributed noises are reduced effectively by Gabor Filters and impulse noises by DMF. the proposed DMF not only can finish its original tasks, it can also join broken fingerprint ridges, fill out the holes of fingerprint images, smooth irregular ridges as well as remove some annoying small artifacts between ridges. Experimental results show our method to be superior to those described in the literature.

Impulse noise still poses challenges in front of researchers today. The removal of impulse noise brings blurring which leads to edges being distorted and image thus being of poor quality. Hence the need is to preserve edges and fine details during filtering. The proposed method consists of noise detection and then removal of detected noise by Improved Adaptive Median Filter using pixels that are not noise themselves in gray level as well as colour images. The pixels are split in two groups, which are noise-free pixels and noisy pixels. In removing out Impulse noise, only noisy pixels are processed. The noiseless pixels are then sent directly to the output image. The proposed method adaptively changes the masking matrix size of the median filter based on the count of the noisy pixels. Computer simulation and analysis have been carried out eventually to analyse the performance of the proposed method with that of Simple Median Filter (SMF), Simple Adaptive Median Filter (SAMF) and Adaptive Switched Median Filter (ASMF). The proposed filter proves to be more efficient in terms of both objective and subjective parameters.

Image processing is one of the most important areas of signal processing. Image processing is applicable for the improvement of pictorial improvement for human perception and autonomous machine application also the efficient storage and transmission. In this paper guided filter is proposed which can be applicable to both images as well as to video. This guided filter has many advantages over the previous version of filter like mean filter, median filter, sobel filter, bilateral filter, etc. Among of those bilateral filter is more popular. But this bilateral filter has certain limitations like gradient reversal effect this introduces false edges in the image. Proposed guided filter can smooth image/video and also preserved the edge that is information at the edges of image/video but this filter has better behaviors near edges. Also the fast implementation of guided filter is possible. This filter also has algorithm implementation regardless of kernel size. Guided filter gives better output than that of bilateral filter after filtering this bilateral filter gives output like cartoon this also a problem with this. The guided filter is both effective and efficient in many applications of computer vision and computer graphics, etc. Filtering techniques are used in image and video processing applications for various technologies.

Despite lots of effort being exerted in designing feature descriptors, it is still challenging to find generalized feature descriptors, with acceptable discrimination ability, which are able to capture prominent features in various image processing applications. To address this issue, we propose a computationally feasible discriminative ternary census transform histogram (DTCTH) for image representation which uses dynamic thresholds to perceive the key properties of a feature descriptor. The code produced by DTCTH is more stable against intensity fluctuation, and it mainly captures the discriminative structural properties of an image by suppressing unnecessary background information. Thus, DTCTH becomes more generalized to be used in different applications with reasonable accuracies. To validate the generalizability of DTCTH, we have conducted rigorous experiments on five different applications considering nine benchmark datasets. The experimental results demonstrate that DTCTH performs as high as 28.08% better than the existing state-of-the-art feature descriptors such as GIST, SIFT, HOG, LBP, CLBP, OC-LBP, LGP, LTP, LAID, and CENTRIST.

This paper proposes a new approach for color transfer between two images. Our method is unique in its consideration of the scene illumination and the constraint that the mapped image must be within the color gamut of the target image. Specifically, our approach first performs a white-balance step on both images to remove color casts caused by different illuminations in the source and target image. We then align each image to share the same ‘white axis’ and perform a gradient preserving histogram matching technique along this axis to match the tone distribution between the two images. We show that this illuminant-aware strategy gives a better result than directly working with the original source and target image’s luminance channel as done by many previous methods. Afterwards, our method performs a full gamut-based mapping technique rather than processing each channel separately. This guarantees that the colors of our transferred image lie within the target gamut. Our experimental results show that this combined illuminant-aware and gamut-based strategy produces more compelling results than previous methods. We detail our approach and demonstrate its effectiveness on a number of examples.

This paper introduces a new approach for optimum auto exposure (AE) based on the high-dynamic-range histogram (HDH) of a scene. The exposure control is optimal in terms of recorded information of the scene. The advantages over AE based on mean values of images will be shown as well as a proof of concept implementation and results. Futhermore possible extensions to this approach are discussed. The consideration of the HDH for auto exposure enables new possibilities for auto exposure control for mutliple-slope cameras. An AE method for multiple-slope cameras is proposed which controls exposure as well as the transition curve parameters in order to record a maximum of information from the scene. It considers controllable dynamic range as well as corse quantization in bright image regions. Key–Words: Optimum Auto Exposure, High Dynamic Range (HDR), multiple-slope camera January 26, 2007

In an underwater scene, wavelength-dependent light absorption and scattering degrade the visibility of images, causing low contrast and distorted color casts. To address this problem, we propose a convolutional neural network based image enhancement model, i.e., UWCNN, which is trained efficiently using a synthetic underwater image database. Unlike the existing works that require the parameters of underwater imaging model estimation or impose inflexible frameworks applicable only for specific scenes, our model directly reconstructs the clear latent underwater image by leveraging on an automatic end-to-end and data-driven training mechanism. Compliant with underwater imaging models and optical properties of underwater scenes, we first synthesize ten different marine image databases. Then, we separately train multiple UWCNN models for each underwater image formation type. Experimental results on real-world and synthetic underwater images demonstrate that the presented method generalizes well on different underwater scenes and outperforms the existing methods both qualitatively and quantitatively. Besides, we conduct an ablation study to demonstrate the effect of each component in our network.


Question: Future outlook on next-generation e-sports infrastructure and examining their advantages.

This paper delves into the evolving role of marketing within hypermedia computer-mediated environments (CMEs), focusing on large-scale, networked environments like the World Wide Web on the Internet. We present a groundbreaking medium to marketers and propose dual structural models of consumer behavior within a CME. Subsequently, we scrutinize the set of testable research hypotheses and marketing implications that emerge from these models. The paper's introduction highlights the paradigm shift in marketing and communication media, driven by the advent of the Internet. Traditionally, marketing media adhered to a passive, one-to-many communication model, with limited customer feedback. The Internet's interactive multimedia many-to-many communication model has disrupted this norm, facilitating discussion groups, multi-player games, file transfer, electronic mail, and information access systems. The paper examines the implications of commercializing hypermedia CMEs, with the World Wide Web on the Internet as the primary global implementation. We define hypermedia CMEs as distributed networks for accessing and providing hypermedia content, with a focus on marketing activities within Web-accessible CMEs. The Internet is a pivotal arena for marketers due to the large volume of business conducted online, surpassing other CMEs. The research is driven by the central thesis that hypermedia CMEs necessitate the development of new marketing concepts and models, given their unique attributes such as machine-interactivity, telepresence, hypermedia, and network navigation, which differentiate them from traditional media. As of December 28, 1994, over 21,700 commercial Internet addresses were active, with a growing number providing Web services. This underscores the significance of understanding and adapting marketing strategies to hypermedia CMEs. The paper by Hoffman & Novak (1995) serves as a foundational text in this area, addressing the conceptual underpinnings of marketing in hypermedia computer-mediated environments.

This paper explores the transformative impact of marketing within hypermedia computer-mediated environments (CMEs), particularly within the context of large-scale, interconnected networks like the World Wide Web on the Internet. Our approach introduces marketers to this revolutionary medium and proposes two models of consumer behavior in a CME. We then analyze the consequent testable research propositions and marketing implications that arise from these models. Traditionally, marketing media followed a passive one-to-many communication model, with limited customer feedback. However, the emergence of the Internet has disrupted this traditional view by introducing an interactive multimedia many-to-many communication model. This model supports various functionalities, including discussion

This study is aimed to investigate primary level students’ attitude and motivation and perceptions in learning English using Kahoot game. According to current development in Malaysian education field, 21st century learning style is more focused and given importance. Thus, Kahoot, game-based learning platform has been used to stimulate students’ from a rural area in southern Malaysia to learn English as their second language more effectively, actively and interestingly. The research design for this study is action research. Nine students were chosen as the target group for this study. The Kahoot game was conducted for three different topics in English after they completed the lesson each day. The data was collected using Attitude and Motivation Test Battery questionnaires consisting of 10 items, interview session with 5 semi-structured questions for three selected students and results of each Kahoot game played by the students. The data was analysed using descriptive analysis. The results of the questionnaires, interview session and results of the game were shown in figures and tables. Findings of the study show that all the nine students were able to engage actively in the game and they were able to master the target language effectively. They enjoy learning English using games and wish to have more games in future.

There are numerous claims that playing computer and video games may be educationally beneficial, but there has been little formal investigation into whether or not the frequency of exposure to such games actually affects academic performance. This paper explores the issue by analysing the relationships between gaming frequency – measured as the amount of time undergraduate students spend playing games in their free time – and their academic performance as measured by their examination marks. Using a sample of 713 students, correlation analyses between gaming frequency and examination performance were conducted for students of varying gaming frequency, study discipline, gender, and general attitudes towards gaming and study. The results reveal that examination marks are in fact negatively correlated with gaming frequency – i.e. frequent gamers generally achieve lower marks than less frequent gamers.

Games are undoubtedly the most successful computer application yet it is not easy to attribute their success to any one particular feature. Nonetheless, when talking about games, gamers and reviewers frequently refer to the immersive experience of the game as an important aspect to be attained. However, it is not clear what immersion is and even if it is a comparable experience between different players and different games. This paper aims to develop more quantifiable and therefore objective measures of immersion. We describe a study into switching from an immersive gaming experience to another task, not in the game world. Though the degree of immersion does seem to have an impact on the ability to perform the task, the experimental approach is complex and possibly quite fragile. We therefore set out hypotheses for a similar experiment with the aim of exploring whether eyetracking and body motion provide better indicators of the degree of immersion.

In this paper, I will describe my intuitions about what makes computer games fun. More detailed descriptions of the experiments and the theory on which this paper is based are given by Malone (1980a, 1980b). My primary goal here is to provide a set of heuristics or guidelines for designers of instructional computer games. I have articulated and organized common sense principles to spark the creativity of instructional designers (see Banet, 1979, for an unstructured list of similar principles). To demonstrate the usefulness of these principles, I have included several applications to actual or proposed instructional games. Throughout the paper I emphasize games with educational uses, but I focus on what makes the games fun, not on what makes them educational.
 Though I will not emphasize the point in this paper, these same ideas can be applied to other educational environments and life situations. In a sense, the categories I will describe constitute a general taxonomy of intrinsic motivation—of what makes an activity fun or rewarding for its own sake rather than for the sake of some external reward (See Lepper and Greene, 1979).
 I think the essential characteristics of good computer games and other intrinsically enjoyable situations can be organized into three categories: challenge, fantasy, and curiosity.

Future functions of vehicles to make driving safer, more comfortable and more exciting rely on suitable in-vehicle networks. Legacy Ethernet extended by AVB to meet recent and future requirements is discussed as a proper candidate. Investigation of its forwarding, synchronization and resource reservation mechanisms are an important prerequisite for the object: The progressive vehicle integration unleashing its whole potential as an in-vehicle network. This paper focuses on AVB's forwarding policy by using Network Calculus as a theory for calculating worst case delays.

Virtual Reality (VR) has finally caught the attention of major technology companies, giving it a significant boost towards becoming market-ready. VR has the capacity to create profoundly engaging experiences by synthesizing highly detailed sensory input in real time, making games the most obvious applications of VR. While the promises of VR may be exciting due to the problems it can solve and new experiences it can offer, there are still numerous issues to be addressed in order to achieve maximal immersion in VR. In this paper, we present the issues encountered during open testing of our applications on commercially available VR goggles and hand input device. The inability to effectively use the hands and feet to control and navigate the environment degrades the level of immersion of VR. With users preferring reliability over intuitiveness, we explore the use of gaze as a substitute input device. Results of experiments conducted on numerous volunteers showed significant improvement in terms of user control.

This paper puts the Internet of Things in a wider context: How it relates to the Future Internet overall, and where the business value lies so that it will become interesting for enterprises to invest in it. Real-World Awareness and Business Process Decomposition are the two major paradigms regarding future business value. The major application domains where the Internet of Things will play an important role and where there are concrete business opportunities are highlighted. But there are also many technical challenges that need to be addressed. These are listed and it is shown how they are tackled by existing research projects with industrial participation.

There is an increasing awareness about the potential of serious games for education and training in many disciplines. However, research still witnesses a lack of methodologies, guidelines and best practices on how to develop effective serious games and how to integrate them in the actual learning and training processes. This process of integration heavily depends on providing and spreading evidence of the effectiveness of serious games This paper reports a user study to evaluate the effectiveness of Icura, a serious game about Japanese culture and etiquette. The evaluation methodology extends the set of instruments used in previous studies by evaluating the effects of the game on raising awareness, by avoiding the selective attention bias and by assessing the medium-term retention. . With this research we aim to provide a handy toolkit for evaluating the effectiveness a serious games for cultural awareness and heritage.

With the increasing rise of professionalism in sport, athletes, teams, and coaches are looking to technology to monitor performance in both games and training in order to find a competitive advantage. The use of inertial sensors has been proposed as a cost effective and adaptable measurement device for monitoring wheelchair kinematics; however, the outcomes are dependent on the reliability of the processing algorithms. Though there are a variety of algorithms that have been proposed to monitor wheelchair propulsion in court sports, they all have limitations. Through experimental testing, we have shown the Attitude and Heading Reference System (AHRS)-based algorithm to be a suitable and reliable candidate algorithm for estimating velocity, distance, and approximating trajectory. The proposed algorithm is computationally inexpensive, agnostic of wheel camber, not sensitive to sensor placement, and can be embedded for real-time implementations. The research is conducted under Griffith University Ethics (GU Ref No: 2016/294).

This study aims to examine the possibility of implementing the Augmented Reality (AR) application in higher education by answering three questions: Which extended faculty at the Saudi Electronic University are familiar with such applications, what the perceptions do they hold toward using it in education, and what barriers do they believe may hinder implementing this technology. An online survey was designed and distributed to faculty members at two colleges selected randomly to collect data from participants. Even though the faculty were at an accepted level of familiarity with this technology, they did not use it in their classes. Results showed that faculty have a positive attitude toward the use of AR and have confidence in its potential to enrich the learning environment. This result is connected to the AR advantages the faculty were in agreement with. Results also showed that faculty have concerns about some barriers that might impact implementation of AR in the education environment, such as the lack of technical support.


Question: Prospective insights into the next-gen e-sports infrastructure and uncovering its advantages.

This paper delves into the impact of computer games on the academic performance of Computer Science (CS) and other students, highlighting the potential pitfalls of excessive gaming. It specifically addresses the concern that an obsession with role-playing games can lead to detrimental outcomes, such as poor grades and the subsequent risk of losing financial support from parents who fund their education. The study underscores the importance of balancing leisure activities, such as gaming, with academic responsibilities to avoid negative consequences on students' academic success and financial stability.

**Question**: Future Perspectives on Next Generation e-Sports Infrastructure and Exploring Their Benefits

**Documents**: The evolving landscape of e-Sports: Challenges and opportunities in the digital age
E-Sports, or electronic sports, have rapidly emerged as a significant cultural and economic force in the digital age. This paper explores the evolution of e-Sports, examining both the challenges and opportunities presented by this growing phenomenon. It discusses the infrastructure required to support e-Sports, including the technological advancements needed to ensure smooth gameplay and spectator experiences. The paper also addresses the social and economic benefits of e-Sports, such as job creation, community building, and the potential for positive youth development. However, it also acknowledges the challenges, such as the need for regulation, addressing health concerns among players, and ensuring accessibility and inclusivity for all participants. The future of e-Sports is bright, but careful planning and consideration are necessary to harness its full potential.

**Similar Documents**: This article provides an in-depth analysis of the burgeoning field of e-Sports within the context of the digital era. As e-Sports continue to gain prominence, the paper scrutinizes the multifaceted challenges and promising opportunities that this sector presents. It delves into the critical infrastructure that is essential for the thriving ecosystem of e-Sports, emphasizing the technological innovations that are pivotal for enhancing both the gaming and viewing experiences. Moreover, the paper illuminates the myriad social and economic advantages associated with e-Sports, including the creation of employment opportunities, the fostering of community engagement, and the potential for constructive youth engagement. However, it also candidly acknowledges the pressing issues that need to be addressed, such as regulatory frameworks, health-related concerns for players, and the imperative for inclusivity. The future of e-Sports is indeed promising, yet it necessitates strategic planning and thoughtful reflection to fully capitalize on its potential.

The WTFast's Gamers Private Network (GPN®) is a client/server solution that makes online games faster. GPN® connects online video-game players with a common game service across a wide-area network. Online games are interactive competitions by individual players who compete in a virtual environment. Response time, latency and its predictability are keys to GPN® success and runs against the vast complexity of internet-wide systems. We have built an experimental network of virtualized GPN® components so as to carefully measure the statistics of latency for distributed Minecraft games and to do so in a controlled laboratory environment. This has led to a better understanding of the coupling between parameters such as: the number of players, the subset of players that are idle or active, the volume of packets exchanged, the size of packets, latency to and from the game servers, and time-series for most of those parameters. In this paper we present a mathematical model of those system game network parameters and show how it leads to: (1) realistic simulation of each of those network or game parameters, without relying on the experimental setup; (2) very large-scale numerical simulation of the game setup so as to explore various internet-wide performance scenarios that: (a) are impossible to isolate from internet “noise” in their real environment and; (b) would require vast supercomputing resources if they were to be simulated exhaustively. We motivate all elements of our mathematical model and estimate the savings in computational costs they will bring for very large-scale simulation of the GPN®. Such simulations will improve quality of service for GPN® systems and their reliability.

A great majority of the existing frameworks are inadequate to address their universal applicability in countries with certain socio-economic and technological settings. Though there is so far no “one size fits all” strategy in implementing eGovernment, there are some essential common elements in the transformation. Therefore, this paper attempts to develop a singular sustainable model based on some theories and the lessons learned from existing e-Participation initiatives of developing and developed countries, so that the benefits of ICT can be maximized and greater participation be ensured.

Creating a design theory for Constructivist Gaming Learning Environment necessitates, among other things, the establishment of design principles. These principles have the potential to help designers produce games, where users achieve higher levels of learning. This paper focuses on twelve design principles: Probing, Distributed, Multiple Routes, Practice, Psychosocial Moratorium, Regime of Competence, Self-Knowledge, Collective Knowledge, Engaging, User Interface Ease of Use, On Demand and Just-in-Time Tutorial, and Achievement. We report on two pilot studies of a qualitative nature in which we test our design principles. Game play testing and observations were carried out on five Massively Multiplayer Online Games (MMOGs): RuneScape, GuildWars, Ragnarok, World of WarCraft, and Final Fantasy XI. Two educational games, Carabella Goes to College and Outbreak at WatersEdge were also observed. Our findings indicate that not all of the popular MMOGs and educational games support all of these principles.

Big data, which is maturing over time, has a high impact in analyzing scenarios and coming up with decision making strategies pertaining to any sector. Consequently the number of applications are also increasing where in the past, they were limited to the confines of company sales departments. In lieu, this paper is primarily focused on applying Data Sciences within the education sector. We will be discussing the overall application to address higher-education issues. We will also present a framework for capturing, analyzing it and concluding on data in order to benefit decision-makers, thus ultimately manifesting in informing design and finalizing policy.

Increasing exposure of children and adolescents to electronic media is a worldwide phenomenon, including in Thailand. To date, few studies examine electronic game play in Thai adolescents. Our research describes the prevalence of electronic game play and examines associations between the time spent engaged in electronic game play and school performance of adolescents in Hat-Yai municipality. A cross-sectional study was conducted among 1,492 adolescents from four secondary schools and one commercial college from January through March 2007, using questionnaires for collecting information about demographic data, school grades, and electronic game play behaviors. The prevalence of electronic game play was 75% in boys and 59% in girls. Twenty-two percent of boys and 8.7% of girls played electronic games every day with more than 2 hours per session. The two most common places of game play were at game shops (71%), followed by at their own home (70%). Using linear regression analysis, the "low user or less than 2 hours per session" game players and females were less likely to have school grades below 3.00 with adjusted odds ratios of 0.44 (95% CI 0.25-0.80, p = 0.004) and 0.49 (95% CI 0.30-0.76, p = 0.005) respectively. This study finds that excessive playing of electronic games is associated with school grades below 3.00.

Blockchain technology has the potential to revolutionize applications and redefine the digital economy.

Purpose: Smartphones facilitate the potential adoption of new mobile applications. The purpose of this research is to study users and non-users of three selected mobile applications, and find out what really drives the intention to use these applications across users and non-users. Design/methodology/approach: The authors measured actual usage of mobile applications in a panel study of 579 Finnish smartphone users, using in-device measurements as an objective way to identify users and non-users. A web-based survey was used in collecting data to test an extended TAM model in explaining intention to use. Findings: Perceived technological barriers negatively affect behavioural control, reflecting people’s assessment of themselves being capable of using the services without trouble. Behavioural control is directly linked to perceived usefulness (except for games) and perceived enjoyment, as hypothesized. Perceived enjoyment and usefulness were generically found to explain intention to use applications for both users and for non-users. Research limitations/implications: With regards to the impact of social norms, the study finds that further research needs to be done in exploring its impact more thoroughly. The dataset of the research, consisting purely of male-dominated, young smartphone users, make the generalization of results difficult. Practical implications: There are differences regarding what drives the usage of different kinds of mobile applications. In this study, map applications and mobile Internet, are driven by more utilitarian motivations, whereas games are more hedonic. It is also clear that not everybody are using applications facilitated by smartphones, and therefore the presented approach of studying users and non-users separately provides a new approach to analyze adoption on a practical level. Originality/value: This research proves that models like TAM should not treat mobile services as a generic concept, but instead to specifically address individual mobile services. The research also demonstrates the unique value of combining objective usage measurements (reflecting actual behaviour) with traditional survey data in more comprehensively modelling service adoption. 2009 Elsevier Ltd. All rights reserved.

OBJECTIVE
To describe the promise and potential of big data analytics in healthcare.

METHODS
The paper describes the nascent field of big data analytics in healthcare, discusses the benefits, outlines an architectural framework and methodology, describes examples reported in the literature, briefly discusses the challenges, and offers conclusions.

RESULTS
The paper provides a broad overview of big data analytics for healthcare researchers and practitioners.

CONCLUSIONS
Big data analytics in healthcare is evolving into a promising field for providing insight from very large data sets and improving outcomes while reducing costs. Its potential is great; however there remain challenges to overcome.

Smart Cities gained importance as a means of making ICT enabled services and applications available to the citizens, companies and authorities that are part of a city's system. It aims at increasing citizens' quality of life, and improving the efficiency and quality of the services provided by governing entities and businesses. This perspective requires an integrated vision of a city and of its infrastructures, in all its components. A Smart City can be taken according to six characteristics: All these domains raise new challenges in security and privacy, since users implicitly expect systems to be secure and privacy-preserving. One of the critical elements is which role(s) the city will take up as an actor within an increasingly complex value network. New players enter the market, actors shift their business strategies, roles change, different types of platforms emerge and vie for market dominance, technological developments create new threats and opportunities, etc. An element related to the trend of platformisation is cloud computing, which is increasingly helping the private sector to reduce cost, increase efficiency, and work smarter. One particular challenge relates to open data business models. Activities necessary for Public Sector Information provision can be identified. The development of efficient and effective e-government is a prerequisite. Transnational authentication systems for citizens and businesses, agreed frameworks for data privacy, and the sharing and collection of individual and business data, are key. Smart Cities need to be able to integrate themselves into national, regional and international infrastructures. Although the implementation aspects depend strongly on the authorities of these infrastructures, European wide recommendations and directives will definitely contribute to accelerate the deployment of Smart Cities. Health, inclusion and assisted living will play an essential role, since the demand for related services is rising, because ageing is changing disease composition. Requirements address a number of technologies, beyond the ones related to mobile and fixed networks. An integrated perspective on healthcare solutions for the near-to long-term can be foreseen, bridging a direct gap in between the health area and the technological development of communications (radio and network components). The needs for mobility in urban areas result into a number of problems, such as traffic congestion and energy consumption, which can be alleviated by exploiting Intelligent Transportation Systems and further adoption of vehicle-to-vehicle and vehicle-to-infrastructure communication networks. The information being managed in this area can be relevant to other domains, which increases its potential. An effective deployment …

Background: This paper presents design and results from preliminary evaluation of Tangible Geometric Games (TAG-Games) for cognitive assessment in young children. The TAG-Games technology employs a set of sensor-integrated cube blocks, called SIG-Blocks, and graphical user interfaces for test administration and real-time performance monitoring. TAG-Games were administered to children from 4 to 8 years of age for evaluating preliminary efficacy of this new technology-based approach. Methods: Five different sets of SIG-Blocks comprised of geometric shapes, segmented human faces, segmented animal faces, emoticons, and colors, were used for three types of TAG-Games, including Assembly, Shape Matching, and Sequence Memory. Computational task difficulty measures were defined for each game and used to generate items with varying difficulty. For preliminary evaluation, TAG-Games were tested on 40 children. To explore the clinical utility of the information assessed by TAG-Games, three subtests of the age-appropriate Wechsler tests (i.e., Block Design, Matrix Reasoning, and Picture Concept) were also administered. Results: Internal consistency of TAG-Games was evaluated by the split-half reliability test. Weak to moderate correlations between Assembly and Block Design, Shape Matching and Matrix Reasoning, and Sequence Memory and Picture Concept were found. The computational measure of task complexity for each TAG-Game showed a significant correlation with participants' performance. In addition, age-correlations on TAG-Game scores were found, implying its potential use for assessing children's cognitive skills autonomously.


Question: Prospective insights into the upcoming e-sports infrastructure of the next generation and investigating their advantages.

Introducing eSports: A Grid-Enabled Collaborative Video Annotation System for Enhanced Online Education

In this paper, we present eSports, an innovative collaborative and synchronous video annotation system designed for a large-scale, cross-platform grid computing environment. This system aims to facilitate computer-supported cooperative work (CSCW) in educational contexts such as remote sports coaching and virtual classrooms. Unlike conventional multimedia annotation tools, eSports offers unique features including real-time live video playback and archiving, snapshot capturing, whiteboard annotation for video snapshots, and the ability to play back video annotations synchronized with the original video streams. The system is built upon the grid-based collaboration paradigm, employing the shared event model with NaradaBrokering—a publish/subscribe-based distributed message passing and event notification system. Beyond detailing the design and implementation of eSports, we also explore its potential applications across various educational settings. We are convinced that eSports significantly enhances online collaborative coaching and learning experiences.

Future Directions in Next-Generation eSports Infrastructure: Uncovering the Benefits

The evolution of eSports infrastructure presents exciting opportunities for innovation in online education and collaborative coaching. As we look ahead, next-generation eSports platforms will increasingly leverage advanced grid computing environments to support real-time, cross-platform collaboration. These systems will enable users to seamlessly interact with live video streams, take snapshots, and annotate content in real-time, all while maintaining synchronization with the original video feed. By adopting a grid-based collaboration paradigm, such as the shared event model using NaradaBrokering, these platforms can facilitate publish/subscribe-based distributed message passing and event notifications, enhancing the collaborative experience. As we explore the potential use cases for these advanced eSports systems in educational settings, we can anticipate improvements in online collaborative coaching and education, making learning more interactive and effective.

The potential for integration of digital games and learning becomes ever more significant recently. One of the goals in educational game design is to create engaging and immersive learning experiences for delivering specified learning goals, outcomes and experiences. However, there is limited number of research done on game usability or quality of game user interface. Failure to design usable game interfaces can interfere with the larger goal of creating a compelling experience for users and can have a negative effect on the overall quality and success of a game. In this paper, we review usability problems identified by previous researchers and propose a history educational game design which includes pedagogical and game design component. Some snapshots of our game module are also presented. Finally we present a usability evaluation method for history educational game design. From our critical literature reviews, we also proposed six constructs which are interface, mechanics, gameplay, playability, feedback and immersion for usability evaluation.

The FuturICT project seeks to use the power of big data, analytic models grounded in complexity science, and the collective intelligence they yield for societal benefit. Accordingly, this paper argues that these new tools should not remain the preserve of restricted 110 The European Physical Journal Special Topics government, scientific or corporate élites, but be opened up for societal engagement and critique. To democratise such assets as a public good, requires a sustainable ecosystem enabling different kinds of stakeholder in society, including but not limited to, citizens and advocacy groups, school and university students, policy analysts, scientists, software developers, journalists and politicians. Our working name for envisioning a sociotechnical infrastructure capable of engaging such a wide constituency is the Global Participatory Platform (GPP). We consider what it means to develop a GPP at the different levels of data, models and deliberation, motivating a framework for different stakeholders to find their ecological niches at different levels within the system, serving the functions of (i) sensing the environment in order to pool data, (ii) mining the resulting data for patterns in order to model the past/present/future, and (iii) sharing and contesting possible interpretations of what those models might mean, and in a policy context, possible decisions. A research objective is also to apply the concepts and tools of complexity science and social science to the project’s own work. We therefore conceive the global participatory platform as a resilient, epistemic ecosystem, whose design will make it capable of selforganization and adaptation to a dynamic environment, and whose structure and contributions are themselves networks of stakeholders, challenges, issues, ideas and arguments whose structure and dynamics can be modelled and analysed.

E-government has become part and parcel of every government’s agenda. Many governments have embraced its significant impacts and influences on governmental operations. As the technology mantra has become more ubiquitous, so government have decided to inaugurate e-government policy in its agencies and departments in order to enhance the quality of services, better transparency and greater accountability. As for Malaysia, the government is inspired by the wave of the e-government, as its establishment can improve the quality of public service delivery, and also its internal operations. This qualitative study will explore the status implementation of e-government initiatives as a case study, and will also provide a comparative evaluation of these findings, using the South Korean government as a benchmark study, given its outstanding performance in e-government. The findings of this study will highlight potential areas for improvement in relation to the public administration perspective and from this comparative approach too, Malaysia can learn some lessons from South Korea’s practices to ensure the success of e-government projects.

Keywords in the ACM Digital Library and IEEE Xplore digital library and in NSF grants anticipate future CS research.

This article briefly describes the advantages and disadvantages of crowdsourcing applications applied to disaster relief coordination. It also discusses several challenges that must be addressed to make crowdsourcing a useful tool that can effectively facilitate the relief progress in coordination, accuracy, and security.

The General Video Game AI framework and competition pose the problem of creating artificial intelligence that can play a wide, and in principle unlimited, range of games. Concretely, it tackles the problem of devising an algorithm that is able to play any game it is given, even if the game is not known a priori. This area of study can be seen as an approximation of General Artificial Intelligence, with very little room for game-dependent heuristics. This talk summarizes the motivation, infrastructure, results and future plans of General Video Game AI, stressing the findings and first conclusions drawn after two editions of our competition, presenting the tracks that will be held in 2016 and outlining our future plans.

From a simple entertainment activity to a learning tool, it is undeniable that video games are one of the most active and relevant areas in today's society. Since their inception, video games experienced an evolution unmatched by almost any other area and today's video games are complex pieces of software built by expensive multidisciplinary teams. Procedural Content Generation (PCG) offers an alternative to manual design of video game content, optimizing the process of development and thus reducing its cost. However, the content that is generated by traditional PCG techniques is usually very generic and it struggles to offer meaningful game experiences to a diverse player base. Recent years have brought some new PCG techniques that try to solve this problem by dynamically adjusting the generation of content to suit the needs of each individual player. The work presented in this paper focuses on the development of a new PCG methodology that aims to close the gap between game developers and their players. This is achieved by providing the developers with relevant real time player and playing context information and thus creating an easier way for developers to adjust their content generation process in run time to better suit the needs of each player. This was achieved by first designing a methodology that models the player, their context and the game. It was also developed a simple game to showcase the potential of such methodology. The end result was a game that adapts some of its content to different types of players and contexts.

The integrity and confidentiality of computer games has long been a concern of game developers, both in preventing players from cheating and from obtaining unlicensed copies of the software. Recently, Intel released SGX, which can provide new security guarantees for software developers to achieve an unprecedented level of software integrity and confidentiality. To explore how SGX can protect a computer game in practice, in this paper we make a first step of exploring new ways to protect the integrity and confidentiality of game code and data, and in doing so we have developed a framework and design principles for integrating games with SGX. We have applied our framework to demonstrate how it can be used to protect a real world computer game.

Recently, several researches concerning with smart and connected communities have been studied. Soon the 4G / 5G technology becomes popular, and cellular base stations will be located densely in the urban space. They may offer intelligent services for autonomous driving, urban environment improvement, disaster mitigation, elderly/disabled people support and so on. Such infrastructure might function as edge servers for disaster support base. In this paper, we enumerate several research issues to be developed in the ICDCS community in the next decade in order for building safe, smart cities resistant to disasters. In particular, we focus on (A) up-to-date urban crowd mobility prediction and (B) resilient disaster information gathering mechanisms based on the edge computing paradigm. We investigate recent related works and projects, and introduce our on-going research work and insight for disaster mitigation.

This paper discusses a technology that is expected to widely spread in the near future, which is the Sixth Sense Technology. With this new technology yet to be introduced in the market, different implementation approaches are discussed. Such approaches are demonstrated through other inventions similar to the Sixth Sense (SS). They all fall into the same category, which is Augmented Reality Technologies. The paper focuses on the possible applications and opportunities of such technology. Furthermore, the implementation approaches are compared and the pros/cons of each approach are explored. Most importantly, technical challenges and open issues regarding each implementation approach are brought out. Furthermore, predictions are made on which approach is expected to succeed in the coming years. Finally, solutions are discussed to improve the Sixth Sense Technology with regards to its implementation approaches to insure new and better ways of human-computer interaction.


Question: Prospective views on the next-gen e-sports infrastructure and uncovering its advantages.

Exploring the Influence of Immersive Engagement on Digital Gaming Dependency

The phenomenon of consumer habit, particularly in the context of repetitive digital engagement, presents a complex and intriguing area of study. While habitual behavior can sometimes escalate into an obsessive pattern, where individuals persist in actions they recognize as detrimental, it's crucial to note that not all consumers succumb to such compulsions. This research delves into the underpinnings of digital gaming dependency by examining the role of immersive engagement, akin to the concept of flow, in fostering addictive behaviors. Our findings from structural equation modeling reveal that repeated engagement in preferred activities has a moderate influence on dependency, supporting the tenets of rational addiction theory. More strikingly, however, is the pronounced impact of immersive engagement—characterized by a heightened state of perceptional distortion and enjoyment—on dependency. This indicates that gamers who have experienced deep immersion are significantly more prone to developing dependency. The study underscores the critical role of emotional states in the development of addictive behaviors within the digital gaming realm.

Creating a design theory for Constructivist Gaming Learning Environment necessitates, among other things, the establishment of design principles. These principles have the potential to help designers produce games, where users achieve higher levels of learning. This paper focuses on twelve design principles: Probing, Distributed, Multiple Routes, Practice, Psychosocial Moratorium, Regime of Competence, Self-Knowledge, Collective Knowledge, Engaging, User Interface Ease of Use, On Demand and Just-in-Time Tutorial, and Achievement. We report on two pilot studies of a qualitative nature in which we test our design principles. Game play testing and observations were carried out on five Massively Multiplayer Online Games (MMOGs): RuneScape, GuildWars, Ragnarok, World of WarCraft, and Final Fantasy XI. Two educational games, Carabella Goes to College and Outbreak at WatersEdge were also observed. Our findings indicate that not all of the popular MMOGs and educational games support all of these principles.

Gamification is a complex and controversial concept. It has been both embraced as a marketing and education revolution, and dismissed as practice of exploitation. Contested within the debate around gamification has been the very concept of what a game is, what the core mechanics of games are, and whether gamification truly mobilises these core mechanics. This paper will challenge the foundation of this debate through reconceptualising gamification not as a simple set of techniques and mechanics, but as a pedagogic heritage, an alternative framework for training and shaping participant behaviour that has at its core the concepts of entertainment and engagement. In doing so it will recontextualise current practices of gamification into a longer and deeper history, and suggest potential pathways for more sophisticated gamification in the future.

Will Augmented Reality (AR) allow us to access digital information, experience others' stories, and thus explore alternate realities? AR has recently attracted attention again due to the rapid advances in related multimedia technologies as well as various glass-type AR display devices. However, in order to widely adopt AR in alternated realities, it is necessary to improve various core technologies and integrate them into an AR platform. Especially, there are several remaining technical challenges such as 1) real-time recognition and tracking of multiple objects while generating an environment map, 2) organic user interface with awareness of user's implicit needs, intentions or emotion as well as explicit requests, 3) immersive multimodal content augmentation and just-in-time information visualization, 4) multimodal interaction and collaboration during augmented telecommunication, etc. In addition, in order to encourage user engagement and enable an AR ecosystem, AR standards should be established that support creating AR content, capturing user experiences, and sharing the captured experiences.

Reading is a hobby to open the knowledge windows. Besides, it can provide the inspiration and spirit to face this life. By this way, concomitant with the technology development, many companies serve the e-book or book in soft file. The system of this book of course will be much easier. No worry to forget bringing the face detection and gesture recognition for human computer interaction book. You can open the device and get the book by on-line.

This paper describes entries to the third Playable Experiences track to be held at the AIIDE conference. We discuss the five entries accepted to the track for 2015, as well as the ongoing development of the track as part

The potential of Serious Games (SGs) in education is widely recognized, and their adoption is significant in particular in children instruction. However, the deployment rate of SGs in higher education (HE) and their proper insertion in meaningful curricula is still quite low. This paper intends to make a first step in the direction of a better characterization of the pedagogical effectiveness of SGs in HE, by providing a qualitative analysis based on our field experience using three games for entrepreneurship, that we have studied in the light of two well established pedagogical paradigms, such as the Revised Bloom’s taxonomy and the Kolb’s Learning stages. In general, we observe that SGs address several goals of the Bloom’s taxonomy, in particular at the lower levels. Moreover, the cyclical nature of the business simulations can be directly mapped to the sequential steps described by Kolb. However, our analysis also shows that SGs have still to significantly evolve in order to become an effective and efficient tool that could be successfully and reliably used in HE. In the light of our experience, we also propose a schema for a proper integration of SGs by supporting different goals in different steps of a formal education process, Our study finally suggests directions for future research in the field.

This study aims to examine the possibility of implementing the Augmented Reality (AR) application in higher education by answering three questions: Which extended faculty at the Saudi Electronic University are familiar with such applications, what the perceptions do they hold toward using it in education, and what barriers do they believe may hinder implementing this technology. An online survey was designed and distributed to faculty members at two colleges selected randomly to collect data from participants. Even though the faculty were at an accepted level of familiarity with this technology, they did not use it in their classes. Results showed that faculty have a positive attitude toward the use of AR and have confidence in its potential to enrich the learning environment. This result is connected to the AR advantages the faculty were in agreement with. Results also showed that faculty have concerns about some barriers that might impact implementation of AR in the education environment, such as the lack of technical support.

The study explores the adoption of an electronic government (e-government) system called electronic district (e-District) system in context of India. The study validates the decomposed theory of planned behaviour (DTPB) to understand the impact of its factors on the potential adopter’s intention to adopt this system. The proposed research model is validated using the data collected from 304 respondents from a state called Bihar of India where this e-government was supposed to be implemented. The data is analysed through regression analysis technique. The empirical findings of the proposed research model indicated the significant relationships of all proposed hypotheses. The study also provides its limitations, future research directions, and implications for theory and practice toward the end.

We present the concept of paraplay: playful activities that take place within the context of an interactive game or other play activity, but outside the activity itself. By critically examining work related to gaming and play goals and motivations we argue that the concept of playfulness should have a stronger role in our understanding of gaming sessions, and particularly social gaming sessions. In order to further understand the role of playfulness in social gaming we conducted an empirical field study of physical console gaming. Six families with a total of 32 participants were provided with an Xbox 360 console, Kinect sensor, and three casual physical video games to play together for a period of approximately two weeks. Participants were instructed to record their social gaming sessions. We conducted video analysis on these recordings as well as interviews with many of the participants. We found numerous types and examples of playfulness within the gaming session even from those who were not actively participating in the game. Drawing on the results of this study we present a taxonomy of paraplay and discuss the ways that playfulness can be exhibited in a social play session. We show that participants in a game situation act within a wider context of playfulness, according to a variety of significant roles ranging from active player through to audience member. We explore these roles and their attributes to provide a rich account of paraplay and its importance in understanding playful activities broadly.

4G is proving good speeds up to 1Gbps. Then why do we need anything more. The problem is that it is not able to provide real time applications. 5G is the name given to the next generation of mobile data connectivity. It will definitely provide great speeds between 10Gbps to 100Gbps and it will have enough capacity. But the thing that separated 5G from 4G is latency; the latency provided by 4G is between 40ms to 60ms, whereas in 5G it will provide ultra latency between 1ms to 10ms. The standards for 5G will be set till 2020 and it will be applicable by 2022/23. In this paper we have discussed about 5G and its advantages, a probable architecture for 5G and some challenges in 5G. The main technology that maybe used in 5G are massive MIMO, millimetre wave communication, device to device communication, beam division multiple access etc. In this paper we have discussed about massive MIMO, channel estimate in massive MIMO, beam division multiple access technique to be used in massive MIMO, antenna selection in massive MIMO, capacity and energy efficiency in massive MIMO. In future 5G is going to be a technology which will be invisible, I will be just there everywhere just like electricity. It is a very good area for research as standards and frequency band for 5G are yet to be standardised.