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  • Open Access

    ARTICLE

    Perceptual Gradient Similarity Deviation for Full Reference Image Quality Assessment

    Manyu Jin1, Tao Wang1, Zexuan Ji1,*, Xiaobo Shen2

    CMC-Computers, Materials & Continua, Vol.56, No.3, pp. 501-515, 2018, DOI:10.3970/cmc.2018.02371

    Abstract Perceptual image quality assessment (IQA) is one of the most indispensable yet challenging problems in image processing and computer vision. It is quite necessary to develop automatic and efficient approaches that can accurately predict perceptual image quality consistently with human subjective evaluation. To further improve the prediction accuracy for the distortion of color images, in this paper, we propose a novel effective and efficient IQA model, called perceptual gradient similarity deviation (PGSD). Based on the gradient magnitude similarity, we proposed a gradient direction selection method to automatically determine the pixel-wise perceptual gradient. The luminance and More >

  • Open Access

    ARTICLE

    Feature Relationships Learning Incorporated Age Estimation Assisted by Cumulative Attribute Encoding

    Qing Tian1,2,3,*, Meng Cao1,2, Tinghuai Ma1,2

    CMC-Computers, Materials & Continua, Vol.56, No.3, pp. 467-482, 2018, DOI:10.3970/cmc.2018.02197

    Abstract The research of human facial age estimation (AE) has attracted increasing attention for its wide applications. Up to date, a number of models have been constructed or employed to perform AE. Although the goal of AE can be achieved by either classification or regression, the latter based methods generally yield more promising results because the continuity and gradualness of human aging can naturally be preserved in age regression. However, the neighbor-similarity and ordinality of age labels are not taken into account yet. To overcome this issue, the cumulative attribute (CA) coding was introduced. Although such More >

  • Open Access

    ARTICLE

    SMK-means: An Improved Mini Batch K-means Algorithm Based on Mapreduce with Big Data

    Bo Xiao1, Zhen Wang2, Qi Liu3,*, Xiaodong Liu3

    CMC-Computers, Materials & Continua, Vol.56, No.3, pp. 365-379, 2018, DOI:10.3970/cmc.2018.01830

    Abstract In recent years, the rapid development of big data technology has also been favored by more and more scholars. Massive data storage and calculation problems have also been solved. At the same time, outlier detection problems in mass data have also come along with it. Therefore, more research work has been devoted to the problem of outlier detection in big data. However, the existing available methods have high computation time, the improved algorithm of outlier detection is presented, which has higher performance to detect outlier. In this paper, an improved algorithm is proposed. The SMK-means More >

  • Open Access

    ARTICLE

    Machine Learning Based Resource Allocation of Cloud Computing in Auction

    Jixian Zhang1, Ning Xie1, Xuejie Zhang1, Kun Yue1, Weidong Li2,*, Deepesh Kumar3

    CMC-Computers, Materials & Continua, Vol.56, No.1, pp. 123-135, 2018, DOI:10.3970/cmc.2018.03728

    Abstract Resource allocation in auctions is a challenging problem for cloud computing. However, the resource allocation problem is NP-hard and cannot be solved in polynomial time. The existing studies mainly use approximate algorithms such as PTAS or heuristic algorithms to determine a feasible solution; however, these algorithms have the disadvantages of low computational efficiency or low allocate accuracy. In this paper, we use the classification of machine learning to model and analyze the multi-dimensional cloud resource allocation problem and propose two resource allocation prediction algorithms based on linear and logistic regressions. By learning a small-scale training More >

  • Open Access

    ARTICLE

    acSB: Anti-Collision Selective-Based Broadcast Protocol in CR-AdHocs

    Yueyue Li1,*, Zhong Huang1, Yugang Ma2, Guangjun Wen1

    CMC-Computers, Materials & Continua, Vol.56, No.1, pp. 35-46, 2018, DOI:10.3970/cmc.2018.03712

    Abstract As a fundamental operation in ad hoc networks, broadcast could achieve efficient message propagations. Particularl y in the cognitive radio ad hoc network where unlicensed users have different sets of available channels, broadcasts are carried out on multiple channels. Accordingly, channel selection and collision avoidance are challenging issues to balance the efficiency against the reliability of broadcasting. In this paper, an anti-collision selective broadcast protocol, called acSB, is proposed. A channel selection algorithm based on limited neighbor information is considered to maximize success rates of transmissions once the sender and receiver have the same channel. More >

  • Open Access

    ARTICLE

    Efficient Secure Data Provenance Scheme in Multimedia Outsourcing and Sharing

    Zhen Yang1,2, Yongfeng Huang1,2,*, Xing Li1,2, Wenyu Wang3

    CMC-Computers, Materials & Continua, Vol.56, No.1, pp. 1-17, 2018, DOI:10.3970/cmc.2018.03697

    Abstract To cope with privacy leakage caused by multimedia outsourcing and sharing, data provenance is used to analyze leaked multimedia and provide reactive accountability. Existing schemes of multimedia provenance are based on watermarking protocols. In an outsourcing scenario, existing schemes face two severe challenges: 1) when data leakage occurs, there exists a probability that data provenance results can be repudiated, in which case data provenance tracking fails; and 2) when outsourced data are shared, data encryption transfer causes key management burden outside the schemes, and privacy leakage threatens users. In this paper, we propose a novel More >

  • Open Access

    ARTICLE

    Weighted Sparse Image Classification Based on Low Rank Representation

    Qidi Wu1, Yibing Li1, Yun Lin1,*, Ruolin Zhou2

    CMC-Computers, Materials & Continua, Vol.56, No.1, pp. 91-105, 2018, DOI:10.3970/cmc.2018.02771

    Abstract The conventional sparse representation-based image classification usually codes the samples independently, which will ignore the correlation information existed in the data. Hence, if we can explore the correlation information hidden in the data, the classification result will be improved significantly. To this end, in this paper, a novel weighted supervised spare coding method is proposed to address the image classification problem. The proposed method firstly explores the structural information sufficiently hidden in the data based on the low rank representation. And then, it introduced the extracted structural information to a novel weighted sparse representation model More >

  • Open Access

    ARTICLE

    An Advanced Quantum-Resistant Signature Scheme for Cloud Based on Eisenstein Ring

    Faguo Wu1,2, Xiao Zhang1,2, Wang Yao1,2, Zhiming Zheng1,2, Lipeng Xiang3, Wanpeng Li4

    CMC-Computers, Materials & Continua, Vol.56, No.1, pp. 19-34, 2018, DOI:10.3970/cmc.2018.02664

    Abstract Signature, widely used in cloud environment, describes the work as readily identifying its creator. The existing signature schemes in the literature mostly rely on the Hardness assumption which can be easily solved by quantum algorithm. In this paper, we proposed an advanced quantum-resistant signature scheme for Cloud based on Eisenstein Ring (ETRUS) which ensures our signature scheme proceed in a lattice with higher density. We proved that ETRUS highly improve the performance of traditional lattice signature schemes. Moreover, the Norm of polynomials decreases significantly in ETRUS which can effectively reduce the amount of polynomials convolution More >

  • Open Access

    ARTICLE

    A New Encryption-then-Compression Scheme on Gray Images Using the Markov Random Field

    Chuntao Wang1,2, Yang Feng1, Tianzheng Li1, Hao Xie1, Goo-Rak Kwon3

    CMC-Computers, Materials & Continua, Vol.56, No.1, pp. 107-121, 2018, DOI:10.3970/cmc.2018.02477

    Abstract Compressing encrypted images remains a challenge. As illustrated in our previous work on compression of encrypted binary images, it is preferable to exploit statistical characteristics at the receiver. Through this line, we characterize statistical correlations between adjacent bitplanes of a gray image with the Markov random field (MRF), represent it with a factor graph, and integrate the constructed MRF factor graph in that for binary image reconstruction, which gives rise to a joint factor graph for gray images reconstruction (JFGIR). By exploiting the JFGIR at the receiver to facilitate the reconstruction of the original bitplanes… More >

  • Open Access

    ARTICLE

    An Image Steganography Algorithm Based on Quantization Index Modulation Resisting Scaling Attacks and Statistical Detection

    Yue Zhang1, Dengpan Ye2, Junjun Gan1, Zhenyu Li3, Qingfeng Cheng1,*

    CMC-Computers, Materials & Continua, Vol.56, No.1, pp. 151-167, 2018, DOI:10.3970/cmc.2018.02464

    Abstract In view of the fact that the current adaptive steganography algorithms are difficult to resist scaling attacks and that a method resisting scaling attack is only for the nearest neighbor interpolation method, this paper proposes an image steganography algorithm based on quantization index modulation resisting both scaling attacks and statistical detection. For the spatial image, this paper uses the watermarking algorithm based on quantization index modulation to extract the embedded domain. Then construct the embedding distortion function of the new embedded domain based on S-UNIWARD steganography, and use the minimum distortion coding to realize the… More >

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