Advances in Multimedia The latest articles from Hindawi Publishing Corporation © 2016 , Hindawi Publishing Corporation . All rights reserved. Classification of Error-Diffused Halftone Images Based on Spectral Regression Kernel Discriminant Analysis Thu, 26 May 2016 07:56:53 +0000 This paper proposes a novel algorithm to solve the challenging problem of classifying error-diffused halftone images. We firstly design the class feature matrices, after extracting the image patches according to their statistics characteristics, to classify the error-diffused halftone images. Then, the spectral regression kernel discriminant analysis is used for feature dimension reduction. The error-diffused halftone images are finally classified using an idea similar to the nearest centroids classifier. As demonstrated by the experimental results, our method is fast and can achieve a high classification accuracy rate with an added benefit of robustness in tackling noise. Zhigao Zeng, Zhiqiang Wen, Shengqiu Yi, Sanyou Zeng, Yanhui Zhu, Qiang Liu, and Qi Tong Copyright © 2016 Zhigao Zeng et al. All rights reserved. Video Traffic Flow Analysis in Distributed System during Interactive Session Sun, 10 Apr 2016 14:47:22 +0000 Cost effective, smooth multimedia streaming to the remote customer through the distributed “video on demand” architecture is the most challenging research issue over the decade. The hierarchical system design is used for distributed network to satisfy more requesting users. The distributed hierarchical network system contains all the local and remote storage multimedia servers. The hierarchical network system is used to provide continuous availability of the data stream to the requesting customer. In this work, we propose a novel data stream that handles the methodology for reducing the connection failure and smooth multimedia stream delivery to the remote customer. The proposed session based single-user bandwidth requirement model presents the bandwidth requirement for any interactive session like pause, move slowly, rewind, skip some of the frame, and move fast with some constant number of frames. The proposed session based optimum storage finding algorithm reduces the search hop count towards the remote storage-data server. The modeling and simulation result shows the better impact over the distributed system architecture. This work presents the novel bandwidth requirement model at the interactive session and gives the trade-off in communication and storage costs for different system resource configurations. Soumen Kanrar and Niranjan Kumar Mandal Copyright © 2016 Soumen Kanrar and Niranjan Kumar Mandal. All rights reserved. Fast HEVC Intramode Decision Based on Hybrid Cost Ranking Wed, 24 Feb 2016 07:09:23 +0000 To improve rate-distortion (R-D) performance, high efficiency video coding (HEVC) increases the intraprediction modes with heavy computational load, and thus the intracoding optimization is highly demanded for real-time applications. According to the conditional probabilities of most probable modes and the correlation of potential candidate subsets, this paper proposes a fast HEVC intramode decision scheme based on the hybrid cost ranking which includes both Hadamard cost and rate-distortion cost. The proposed scheme utilizes the coded results of the modified rough mode decision and the neighboring prediction units so as to obtain a potential candidate subset and then conditionally selects the optimal mode through early likelihood decision and hybrid cost ranking. By the experiment-driven methodology, the proposed scheme implements the early termination if the best mode from the candidate subset is equal to one or two neighboring intramodes. The experimental results demonstrate that the proposed scheme averagely provides about 23.7% encoding speedup with just 0.82% BD-rate loss in comparison with default fast intramode decision in HM16.0. Compared to other fast intramode decision schemes, the proposed scheme also significantly reduces intracoding time while maintaining similar R-D performance for the all-intraconfiguration in HM16.0 Main profile. Hao Liu and Yuexin Jie Copyright © 2016 Hao Liu and Yuexin Jie. All rights reserved. Enhancement of Video Streaming in Distributed Hybrid Architecture Mon, 22 Feb 2016 09:04:47 +0000 Pure Peer to Peer (P2P) network requires enhancing transportation of chunk video objects to the proxy server in the mesh network. The rapid growth of video on demand user brings congestion at the proxy server and on the overall network. The situation needs efficient content delivery procedure, to the video on demand viewer from the distributed storage. In general scenario, if the proxy server does not possess the required video stream or the chunk of that said video, then the same can be smoothly and rapidly streamed to the viewer. This paper has shown that multitier mesh shaped hybrid architecture composed of P2P and mesh architecture increase the number of requests served by the dynamic environment in comparison with the static environment. Optimized storage finding path search reduces the unnecessary query forward and hence increases the size of content delivery to the desired location. Soumen Kanrar and Niranjan Kumar Mandal Copyright © 2016 Soumen Kanrar and Niranjan Kumar Mandal. All rights reserved. Nonintrusive Method Based on Neural Networks for Video Quality of Experience Assessment Wed, 27 Jan 2016 13:21:18 +0000 The measurement and evaluation of the QoE (Quality of Experience) have become one of the main focuses in the telecommunications to provide services with the expected quality for their users. However, factors like the network parameters and codification can affect the quality of video, limiting the correlation between the objective and subjective metrics. The above increases the complexity to evaluate the real quality of video perceived by users. In this paper, a model based on artificial neural networks such as BPNNs (Backpropagation Neural Networks) and the RNNs (Random Neural Networks) is applied to evaluate the subjective quality metrics MOS (Mean Opinion Score) and the PSNR (Peak Signal Noise Ratio), SSIM (Structural Similarity Index Metric), VQM (Video Quality Metric), and QIBF (Quality Index Based Frame). The proposed model allows establishing the QoS (Quality of Service) based in the strategy Diffserv. The metrics were analyzed through Pearson’s and Spearman’s correlation coefficients, RMSE (Root Mean Square Error), and outliers rate. Correlation values greater than 90% were obtained for all the evaluated metrics. Diego José Luis Botia Valderrama and Natalia Gaviria Gómez Copyright © 2016 Diego José Luis Botia Valderrama and Natalia Gaviria Gómez. All rights reserved. The Harmonic Walk: An Interactive Physical Environment to Learn Tonal Melody Accompaniment Sun, 10 Jan 2016 08:22:04 +0000 The Harmonic Walk is an interactive physical environment designed for learning and practicing the accompaniment of a tonal melody. Employing a highly innovative multimedia system, the application offers to the user the possibility of getting in touch with some fundamental tonal music features in a very simple and readily available way. Notwithstanding tonal music is very common in our lives, unskilled people as well as music students and even professionals are scarcely conscious of what these features actually are. The Harmonic Walk, through the body movement in space, can provide all these users a live experience of tonal melody structure, chords progressions, melody accompaniment, and improvisation. Enactive knowledge and embodied cognition allow the user to build an inner map of these musical features, which can be acted by moving on the active surface with a simple step. Thorough assessment tests with musicians and nonmusicians high school students could prove the high communicative power and efficiency of the Harmonic Walk application both in improving musical knowledge and in accomplishing complex musical tasks. Marcella Mandanici, Antonio Rodà, and Sergio Canazza Copyright © 2016 Marcella Mandanici et al. All rights reserved. Performances Evaluation of a Novel Hadoop and Spark Based System of Image Retrieval for Huge Collections Wed, 16 Dec 2015 06:57:19 +0000 A novel system of image retrieval, based on Hadoop and Spark, is presented. Managing and extracting information from Big Data is a challenging and fundamental task. For these reasons, the system is scalable and it is designed to be able to manage small collections of images as well as huge collections of images. Hadoop and Spark are based on the MapReduce framework, but they have different characteristics. The proposed system is designed to take advantage of these two technologies. The performances of the proposed system are evaluated and analysed in terms of computational cost in order to understand in which context it could be successfully used. The experimental results show that the proposed system is efficient for both small and huge collections. Luca Costantini and Raffaele Nicolussi Copyright © 2015 Luca Costantini and Raffaele Nicolussi. All rights reserved. IPTV Service Framework Based on Secure Authentication and Lightweight Content Encryption for Screen-Migration in Cloud Computing Thu, 26 Nov 2015 06:57:21 +0000 These days, the advancing of smart devices (e.g. smart phones, tablets, PC, etc.) capabilities and the increase of internet bandwidth enables IPTV service provider to extend their services to smart mobile devices. User can just receive their IPTV service using any smart devices by accessing the internet via wireless network from anywhere anytime in the world which is convenience for users. However, wireless network communication has well a known critical security threats and vulnerabilities to user smart devices and IPTV service such as user identity theft, reply attack, MIM attack, and so forth. A secure authentication for user devices and multimedia protection mechanism is necessary to protect both user devices and IPTV services. As result, we proposed framework of IPTV service based on secure authentication mechanism and lightweight content encryption method for screen-migration in Cloud computing. We used cryptographic nonce combined with user ID and password to authenticate user device in any mobile terminal they passes by. In addition we used Lightweight content encryption to protect and reduce the content decode overload at mobile terminals. Our proposed authentication mechanism reduces the computational processing by 30% comparing to other authentication mechanism and our lightweight content encryption reduces encryption delay to 0.259 second. Aymen Abdullah Alsaffar, Young-Rok Shin, and Eui-Nam Huh Copyright © 2015 Aymen Abdullah Alsaffar et al. All rights reserved. Sparsity for Image Denoising with Local and Global Priors Wed, 04 Nov 2015 06:28:13 +0000 We propose a sparsity based approach to remove additive white Gaussian noise from a given image. To achieve this goal, we combine the local prior and global prior together to recover the noise-free values of pixels. The local prior depends on the neighborhood relationships of a search window to help maintain edges and smoothness. The global prior is generated from a hierarchical sparse representation to help eliminate the redundant information and preserve the global consistency. In addition, to make the correlations between pixels more meaningful, we adopt Principle Component Analysis to measure the similarities, which can be both propitious to reduce the computational complexity and improve the accuracies. Experiments on the benchmark image set show that the proposed approach can achieve superior performance to the state-of-the-art approaches both in accuracy and perception in removing the zero-mean additive white Gaussian noise. Xiaoni Gao, Mei Yu, Jianrong Wang, and Jianguo Wei Copyright © 2015 Xiaoni Gao et al. All rights reserved. Personality, Gender, and Age as Predictors of Media Richness Preference Tue, 20 Oct 2015 14:09:18 +0000 Media richness, the degree to which a specific media transmits information in multiple channels, is an important concept as the number of available multimedia communication methods increases regularly. Individuals differ in their preferences for media richness which may influence their choice of communication multimedia in a given situation. These preferences can influence how successful their communication efforts will be. This exploratory study of 299 adults (ages 16–84) with at least a basic ability to compute examines the relationship between multimedia preference and age, gender, and personality traits. Males and people with higher levels of extraversion and agreeableness were found to have a higher preference for media richness. Age was not a significant predictor of media richness preference. David R. Dunaetz, Timothy C. Lisk, and Matthew Minsuk Shin Copyright © 2015 David R. Dunaetz et al. All rights reserved. Compact Local Directional Texture Pattern for Local Image Description Mon, 07 Sep 2015 11:10:15 +0000 This paper presents an effective local image feature region descriptor, called CLDTP descriptor (Compact Local Directional Texture Pattern), and its application in image matching and object recognition. The CLDTP descriptor encodes the directional and contrast information in a local region, so it contains the gradient orientation information and the gradient magnitude information. As the dimension of the CLDTP histogram is much lower than the dimension of the LDTP histogram, the CLDTP descriptor has higher computational efficiency and it is suitable for image matching. Extensive experiments have validated the effectiveness of the designed CLDTP descriptor. Hui Zeng, Rui Zhang, Mingming Huang, and Xiuqing Wang Copyright © 2015 Hui Zeng et al. All rights reserved. Advanced Issues on Topic Detection, Tracking, and Trend Analysis for Social Multimedia Tue, 04 Aug 2015 13:57:06 +0000 Seungmin Rho, Wenny Rahayu, and Uyen Trang Nguyen Copyright © 2015 Seungmin Rho et al. All rights reserved. Supporting Image Search with Tag Clouds: A Preliminary Approach Tue, 04 Aug 2015 11:33:11 +0000 Algorithms and techniques for searching in collections of data address a challenging task, since they have to bridge the gap between the ways in which users express their interests, through natural language expressions or keywords, and the ways in which data is represented and indexed. When the collections of data include images, the task becomes harder, mainly for two reasons. From one side the user expresses his needs through one medium (text) and he will obtain results via another medium (some images). From the other side, it can be difficult for a user to understand the results retrieved; that is why a particular image is part of the result set. In this case, some techniques for analyzing the query results and giving to the users some insight into the content retrieved are needed. In this paper, we propose to address this problem by coupling the image result set with a tag cloud of words describing it. Some techniques for building the tag cloud are introduced and two application scenarios are discussed. Francesco Guerra, Giovanni Simonini, and Maurizio Vincini Copyright © 2015 Francesco Guerra et al. All rights reserved. An Empirical Analysis of Technology Transfer of National R&D Projects in South Korea Tue, 04 Aug 2015 11:10:35 +0000 This study is aimed at seeking policy implications for the policy makers of South Korean government and finding a direction to support R&D institutions in performing R&D activities more efficiently, by analyzing the factors influencing technology transfer of the national R&D projects. The data retrieved from NTIS (National Science & Technology Information Service) was used in analyzing the results of 575 projects with 1,903 cases of technology transfer, performed by the Ministry of Science, ICT and Future Planning, between 2002 and 2012. We found that there were significant differences between the government funded institutions and the universities and between basic R&D and applied ones. We also discovered that the government funded institutions did not necessarily take a better position than the universities in terms of the quantity of technology transfer. Lastly, the applied R&D of the universities was very vulnerable in terms of technology transfer. Mi-Sun Kim, Dong-Ho Shin, Jae-Soo Kim, and Byeong-Hee Lee Copyright © 2015 Mi-Sun Kim et al. All rights reserved. Development of Ontology and 3D Software for the Diseases of Spine Tue, 04 Aug 2015 11:04:16 +0000 KISTI is carrying out an e-Spine project for spinal diseases to prepare for the aged society, so-called NAP. The purpose of the study is to build a spine ontology that represents the anatomical structure and disease information which is compatible with simulation model of KISTI. The final use of the ontology includes diagnosis of diseases and setting treatment directions by the clinicians. The ontology was represented using 3D software. Twenty diseases were selected to be represented after discussions with a spine specialist. Several ontology studies were reviewed, reference books were selected for each disease and were organized in MS Excel. All the contents were then reviewed by the specialists. Altova SemanticWorks and Protégé were used to code spine ontology with OWL Full model. Links to the images from KISTI and sample images of diseases were included in the ontology. The OWL ontology was also reviewed by the specialists again with Protégé. We represented unidirectional ontology from anatomical structure to disease, images, and treatment. The ontology was human understandable. It would be useful for the education of medical students or residents studying diseases of spine. But in order for the computer to understand the ontology, a new model with OWL DL or Lite is needed. Seungbock Lee, Sangho Lee, Dongmin Seo, Kwan-Hee Yoo, and Sukil Kim Copyright © 2015 Seungbock Lee et al. All rights reserved. Performance Comparison of OpenMP, MPI, and MapReduce in Practical Problems Tue, 04 Aug 2015 06:40:03 +0000 With problem size and complexity increasing, several parallel and distributed programming models and frameworks have been developed to efficiently handle such problems. This paper briefly reviews the parallel computing models and describes three widely recognized parallel programming frameworks: OpenMP, MPI, and MapReduce. OpenMP is the de facto standard for parallel programming on shared memory systems. MPI is the de facto industry standard for distributed memory systems. MapReduce framework has become the de facto standard for large scale data-intensive applications. Qualitative pros and cons of each framework are known, but quantitative performance indexes help get a good picture of which framework to use for the applications. As benchmark problems to compare those frameworks, two problems are chosen: all-pairs-shortest-path problem and data join problem. This paper presents the parallel programs for the problems implemented on the three frameworks, respectively. It shows the experiment results on a cluster of computers. It also discusses which is the right tool for the jobs by analyzing the characteristics and performance of the paradigms. Sol Ji Kang, Sang Yeon Lee, and Keon Myung Lee Copyright © 2015 Sol Ji Kang et al. All rights reserved. Coevolution of Artificial Agents Using Evolutionary Computation in Bargaining Game Mon, 03 Aug 2015 14:19:11 +0000 Analysis of bargaining game using evolutionary computation is essential issue in the field of game theory. This paper investigates the interaction and coevolutionary process among heterogeneous artificial agents using evolutionary computation (EC) in the bargaining game. In particular, the game performance with regard to payoff through the interaction and coevolution of agents is studied. We present three kinds of EC based agents (EC-agent) participating in the bargaining game: genetic algorithm (GA), particle swarm optimization (PSO), and differential evolution (DE). The agents’ performance with regard to changing condition is compared. From the simulation results it is found that the PSO-agent is superior to the other agents. Sangwook Lee Copyright © 2015 Sangwook Lee. All rights reserved. Preprocessing Techniques for High-Efficiency Data Compression in Wireless Multimedia Sensor Networks Mon, 03 Aug 2015 14:03:19 +0000 We have proposed preprocessing techniques for high-efficiency data compression in wireless multimedia sensor networks. To do this, we analyzed the characteristics of multimedia data under the environment of wireless multimedia sensor networks. The proposed preprocessing techniques consider the characteristics of sensed multimedia data to perform the first stage preprocessing by deleting the low priority bits that do not affect the image quality. The second stage preprocessing is also performed for the undeleted high priority bits. By performing these two-stage preprocessing techniques, it is possible to reduce the multimedia data size in large. To show the superiority of our techniques, we simulated the existing multimedia data compression scheme with/without our preprocessing techniques. Our experimental results show that our proposed techniques increase compression ratio while reducing compression operations compared to the existing compression scheme without preprocessing techniques. Junho Park and Jaesoo Yoo Copyright © 2015 Junho Park and Jaesoo Yoo. All rights reserved. Security Requirements for Multimedia Archives Mon, 03 Aug 2015 13:32:11 +0000 With the explosive growth of various multimedia contents, digital archives are used to store those contents accordingly. In contrast to the traditional storage systems in which data lifetime is measured in months or years, data lifetime in the archive is measured in decades. This longevity of contents causes new security issues that threat the archive systems. In this paper, we discuss these new security issues in perspective. And we suggest some security requirements for digital archives. Sang Bae Park Copyright © 2015 Sang Bae Park. All rights reserved. Discovering Congested Routes Using Vehicle Trajectories in Road Networks Mon, 03 Aug 2015 13:29:55 +0000 The popular route recommendation and traffic monitoring over the road networks have become important in the location-based services. The schemes to find out the congested routes were proposed by considering the number of vehicles in a road segment. However, the existing schemes do not consider the features of each road segment such as width, length, and direction in a road network. Furthermore, the existing schemes fail to consider the average moving speed of vehicles. Therefore, they can detect the incorrect density routes. To overcome such problems, we propose a new discovering scheme of congested routes through the analysis of vehicle trajectories in a road network. The proposed scheme divides each road into segments with different width and length in a road network. And then, the congested road segment is detected through the saturation degree of the road segment and the average moving speed of vehicles in the road segment. Finally, we compute the final congested routes by using a clustering scheme. The experimental results have shown that the proposed scheme can efficiently discover the congested routes in the different directions of the roads. Kyoung Soo Bok, He Li, Jong Tae Lim, and Jae Soo Yoo Copyright © 2015 Kyoung Soo Bok et al. All rights reserved. Study on Strengthening Plan of Safety Network CCTV Monitoring by Steganography and User Authentication Mon, 03 Aug 2015 12:52:45 +0000 Recently, as the utilization of CCTV (closed circuit television) is emerging as an issue, the studies on CCTV are receiving much attention. Accordingly, due to the development of CCTV, CCTV has IP addresses and is connected to network; it is exposed to many threats on the existing web environment. In this paper, steganography is utilized to confirm the Data Masquerading and Data Modification and, in addition, to strengthen the security; the user information is protected based on PKI (public key infrastructure), SN (serial number), and R value (random number) attributed at the time of login and the user authentication protocol to block nonauthorized access of malicious user in network CCTV environment was proposed. This paper should be appropriate for utilization of user infringement-related CCTV where user information protection-related technology is not applied for CCTV in the future. Jung-oh Park and Sanggeun Kim Copyright © 2015 Jung-oh Park and Sanggeun Kim. All rights reserved. High-Level Codewords Based on Granger Causality for Video Event Detection Tue, 23 Jun 2015 06:20:45 +0000 Video event detection is a challenging problem in many applications, such as video surveillance and video content analysis. In this paper, we propose a new framework to perceive high-level codewords by analyzing temporal relationship between different channels of video features. The low-level vocabulary words are firstly generated after different audio and visual feature extraction. A weighted undirected graph is constructed by exploring the Granger Causality between low-level words. Then, a greedy agglomerative graph-partitioning method is used to discover low-level word groups which have similar temporal pattern. The high-level codebooks representation is obtained by quantification of low-level words groups. Finally, multiple kernel learning, combined with our high-level codewords, is used to detect the video event. Extensive experimental results show that the proposed method achieves preferable results in video event detection. Shao-nian Huang, Dong-jun Huang, and Mansoor Ahmed Khuhro Copyright © 2015 Shao-nian Huang et al. All rights reserved. A New Information Hiding Method Based on Improved BPCS Steganography Thu, 26 Mar 2015 07:31:30 +0000 Bit-plane complexity segmentation (BPCS) steganography is advantageous in its capacity and imperceptibility. The important step of BPCS steganography is how to locate noisy regions in a cover image exactly. The regular method, black-and-white border complexity, is a simple and easy way, but it is not always useful, especially for periodical patterns. Run-length irregularity and border noisiness are introduced in this paper to work out this problem. Canonical Cray coding (CGC) is also used to replace pure binary coding (PBC), because CGC makes use of characteristic of human vision system. Conjugation operation is applied to convert simple blocks into complex ones. In order to contradict BPCS steganalysis, improved BPCS steganography algorithm adopted different bit-planes with different complexity. The higher the bit-plane is, the smaller the complexity is. It is proven that the improved BPCS steganography is superior to BPCS steganography by experiment. Shuliang Sun Copyright © 2015 Shuliang Sun. All rights reserved. Video Superresolution Reconstruction Using Iterative Back Projection with Critical-Point Filters Based Image Matching Thu, 12 Mar 2015 06:22:33 +0000 To improve the spatial resolution of reconstructed images/videos, this paper proposes a Superresolution (SR) reconstruction algorithm based on iterative back projection. In the proposed algorithm, image matching using critical-point filters (CPF) is employed to improve the accuracy of image registration. First, a sliding window is used to segment the video sequence. CPF based image matching is then performed between frames in the window to obtain pixel-level motion fields. Finally, high-resolution (HR) frames are reconstructed based on the motion fields using iterative back projection (IBP) algorithm. The CPF based registration algorithm can adapt to various types of motions in real video scenes. Experimental results demonstrate that, compared to optical flow based image matching with IBP algorithm, subjective quality improvement and an average PSNR score of 0.53 dB improvement are obtained by the proposed algorithm, when applied to video sequence. Yixiong Zhang, Mingliang Tao, Kewei Yang, and Zhenmiao Deng Copyright © 2015 Yixiong Zhang et al. All rights reserved. An Improved Saliency Detection Approach for Flying Apsaras in the Dunhuang Grotto Murals, China Tue, 24 Feb 2015 06:40:29 +0000 Saliency can be described as the ability of an item to be detected from its background in any particular scene, and it aims to estimate the probable location of the salient objects. Due to the salient map that computed by local contrast features can extract and highlight the edge parts including painting lines of Flying Apsaras, in this paper, we proposed an improved approach based on a frequency-tuned method for visual saliency detection of Flying Apsaras in the Dunhuang Grotto Murals, China. This improved saliency detection approach comprises three important steps: (1) image color and gray channel decomposition; (2) gray feature value computation and color channel convolution; (3) visual saliency definition based on normalization of previous visual saliency and spatial attention function. Unlike existing approaches that rely on many complex image features, this proposed approach only used local contrast and spatial attention information to simulate human’s visual attention stimuli. This improved approach resulted in a much more efficient salient map in the aspect of computing performance. Furthermore, experimental results on the dataset of Flying Apsaras in the Dunhuang Grotto Murals showed that the proposed visual saliency detection approach is very effective when compared with five other state-of-the-art approaches. Zhong Chen, Shengwu Xiong, Qingzhou Mao, Zhixiang Fang, and Xiaohan Yu Copyright © 2015 Zhong Chen et al. All rights reserved. Improving Shape Retrieval by Integrating AIR and Modified Mutual NN Graph Wed, 28 Jan 2015 11:54:45 +0000 In computer vision, image retrieval remained a significant problem and recent resurgent of image retrieval also relies on other postprocessing methods to improve the accuracy instead of solely relying on good feature representation. Our method addressed the shape retrieval of binary images. This paper proposes a new integration scheme to best utilize feature representation along with contextual information. For feature representation we used articulation invariant representation; dynamic programming is then utilized for better shape matching followed by manifold learning based postprocessing modified mutual NN graph to further improve the similarity score. We conducted extensive experiments on widely used MPEG-7 database of shape images by so-called bulls-eye score with and without normalization of modified mutual NN graph which clearly indicates the importance of normalization. Finally, our method demonstrated better results compared to other methods. We also computed the computational time with another graph transduction method which clearly shows that our method is computationally very fast. Furthermore, to show consistency of postprocessing method, we also performed experiments on challenging ORL and YALE face datasets and improved baseline results. Nouman Qadeer, Dongting Hu, Xiabi Liu, Shahzad Anwar, and Malik Saad Sultan Copyright © 2015 Nouman Qadeer et al. All rights reserved. A Rate-Distortion Optimized Coding Method for Region of Interest in Scalable Video Coding Mon, 12 Jan 2015 06:45:49 +0000 The support for region of interest (ROI) browsing, which allows dropping background part of video bitstreams, is a desirable feature for video applications. With the help of the slice group technique provided by H.264/SVC, rectangular ROI areas can be encoded into separate ROI slices. Additionally, by imposing certain constraints on motion estimation, ROI part of the bitstream can be decoded without background slices of the same layer. However, due to the additional spatial and temporal constraints applied to the encoder, overall coding efficiency would be significantly decreased. In this paper, a rate-distortion optimized (RDO) encoding scheme is proposed to improve the coding efficiency of ROI slices. When background slices are discarded, the proposed method uses base layer information to generate the prediction signal of the enhancement layer. Thus, the temporal constraints can be loosened during the encoding process. To do it in this way, the possible mismatch between generated reference frames and original ones is also considered during rate-distortion optimization so that a reasonable trade-off between coding efficiency and decoding drift can be made. Besides, a new Lagrange multiplier derivation method is developed for further coding performance improvement. Experimental results demonstrate that the proposed method achieves significant bitrate saving compared to existing methods. Hongtao Wang, Dong Zhang, and Houqiang Li Copyright © 2015 Hongtao Wang et al. All rights reserved. A Simple and Robust Gray Image Encryption Scheme Using Chaotic Logistic Map and Artificial Neural Network Wed, 31 Dec 2014 00:10:35 +0000 A robust gray image encryption scheme using chaotic logistic map and artificial neural network (ANN) is introduced. In the proposed method, an external secret key is used to derive the initial conditions for the logistic chaotic maps which are employed to generate weights and biases matrices of the multilayer perceptron (MLP). During the learning process with the backpropagation algorithm, ANN determines the weight matrix of the connections. The plain image is divided into four subimages which are used for the first diffusion stage. The subimages obtained previously are divided into the square subimage blocks. In the next stage, different initial conditions are employed to generate a key stream which will be used for permutation and diffusion of the subimage blocks. Some security analyses such as entropy analysis, statistical analysis, and key sensitivity analysis are given to demonstrate the key space of the proposed algorithm which is large enough to make brute force attacks infeasible. Computing validation using experimental data with several gray images has been carried out with detailed numerical analysis, in order to validate the high security of the proposed encryption scheme. Adelaïde Nicole Kengnou Telem, Colince Meli Segning, Godpromesse Kenne, and Hilaire Bertrand Fotsin Copyright © 2014 Adelaïde Nicole Kengnou Telem et al. All rights reserved. A Natural Image Pointillism with Controlled Ellipse Dots Wed, 24 Dec 2014 00:10:04 +0000 This paper presents an image-based artistic rendering algorithm for the automatic Pointillism style. At first, ellipse dot locations are randomly generated based on a source image; then dot orientations are precalculated with help of a direction map; a saliency map of the source image decides long and short radius of the ellipse dot. At last, the rendering runs layer-by-layer from large size dots to small size dots so as to reserve the detailed parts of the image. Although only ellipse dot shape is adopted, the final Pointillism style performs well because of variable characteristics of the dot. Dongxiang Chi Copyright © 2014 Dongxiang Chi. All rights reserved. Automatic Image Tagging Model Based on Multigrid Image Segmentation and Object Recognition Mon, 22 Dec 2014 09:21:03 +0000 Since rapid growth of Internet technologies and mobile devices, multimedia data such as images and videos are explosively growing on the Internet. Managing large scale multimedia data with correct tags and annotations is very important task. Incorrect tags and annotations make it hard to manage multimedia data. Accurate tags and annotation ease management of multimedia data and give high quality retrieve results. Fully manual image tagging which is tagged by user will be most accurate tags when the user tags correct information. Nevertheless, most of users do not make effort on task of tagging. Therefore, we suffer from lots of noisy tags. Best solution for accurate image tagging is to tag image automatically. Robust automatic image tagging models are proposed by many researchers and it is still most interesting research field these days. Since there are still lots of limitations in automatic image tagging models, we propose efficient automatic image tagging model using multigrid based image segmentation and feature extraction method. Our model can improve the object descriptions of images and image regions. Our method is tested with Corel dataset and the result showed that our model performance is efficient and effective compared to other models. Woogyoung Jun, Yillbyung Lee, and Byoung-Min Jun Copyright © 2014 Woogyoung Jun et al. All rights reserved.