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  • 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 and deriving theoretically the sum-product… 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 embedding of the secret messages.… More >

  • Open Access

    ARTICLE

    On Hiding Secret Information in Medium Frequency DCT Components Using Least Significant Bits Steganography

    Sahib Khan1,*, M A Irfan1, Arslan Arif1, Syed Tahir Hussain Rizvi2, Asma Gul3, Muhammad Naeem4, Nasir Ahmad5

    CMES-Computer Modeling in Engineering & Sciences, Vol.118, No.3, pp. 529-546, 2019, DOI:10.31614/cmes.2019.06179

    Abstract This work presents a new method of data hiding in digital images, in discrete cosine transform domain. The proposed method uses the least significant bits of the medium frequency components of the cover image for hiding the secret information, while the low and high frequency coefficients are kept unaltered. The unaltered low frequency DCT coefficients preserves the quality of the smooth region of the cover image, while no changes in the high DCT coefficient preserve the quality of the edges. As the medium frequency components have less contribution towards energy and image details, so the modification of these coefficients for… More >

  • Open Access

    ARTICLE

    A Survey of Image Information Hiding Algorithms Based on Deep Learning

    Ruohan Meng1,2,*, Qi Cui1,2, Chengsheng Yuan1,2,3

    CMES-Computer Modeling in Engineering & Sciences, Vol.117, No.3, pp. 425-454, 2018, DOI:10.31614/cmes.2018.04765

    Abstract With the development of data science and technology, information security has been further concerned. In order to solve privacy problems such as personal privacy being peeped and copyright being infringed, information hiding algorithms has been developed. Image information hiding is to make use of the redundancy of the cover image to hide secret information in it. Ensuring that the stego image cannot be distinguished from the cover image, and sending secret information to receiver through the transmission of the stego image. At present, the model based on deep learning is also widely applied to the field of information hiding. This… More >

  • Open Access

    ARTICLE

    Pose Estimation of Space Targets Based on Model Matching for Large-Aperture Ground-Based Telescopes

    Zhengwei Li1,2, Jianli Wang1,*, Tao Chen1, Bin Wang1, Yuanhao Wu1

    CMES-Computer Modeling in Engineering & Sciences, Vol.117, No.2, pp. 271-286, 2018, DOI:10.31614/cmc.2018.04005

    Abstract With the development of adaptive optics and post restore processing techniques, large aperture ground-based telescopes can obtain high-resolution images (HRIs) of targets. The pose of the space target can be estimated from HRIs by several methods. As the target features obtained from the image are unstable, it is difficult to use existing methods for pose estimation. In this paper a method based on real-time target model matching to estimate the pose of space targets is proposed. First, the physically-constrained iterative deconvolution algorithm is used to obtain HRIs of the space target. Second, according to the 3D model, the ephemeris data,… More >

  • Open Access

    ARTICLE

    Despeckling of Ultrasound Images Using Modified Local Statistics Mean Variance Filter

    Ranu Gupta1,3,*, Rahul Pachauri2,3, Ashutosh Singh1,4

    CMES-Computer Modeling in Engineering & Sciences, Vol.114, No.1, pp. 19-32, 2018, DOI:10.3970/cmes.2018.114.019

    Abstract This article presents an improved method of despeckling the ultrasound medical images. In this paper a modified local statistics mean variance filter method has been proposed. In the proposed method, more consideration is given to local statistics since local statistical features are more important rather than global features.Various parameters like mean square error, peak signal to noise ratio, quality index, and structural similarity index measure are calculated to analyze the quality of the despeckled image. More >

  • Open Access

    ARTICLE

    Real-Time Moving Targets Detection in Dynamic Scenes

    Fan Li1, Yang Yang

    CMES-Computer Modeling in Engineering & Sciences, Vol.107, No.2, pp. 103-124, 2015, DOI:10.3970/cmes.2015.107.103

    Abstract The shift of the camera leads to unsteadiness of backgrounds in video sequences. The motion of camera will results in mixture of backgrounds and foregrounds motion. So it is a challenge for targets detection in dynamic scenes. A realtime moving target detection algorithm with low complexity in dynamic scenes is proposed in this paper. Sub-block based image registration is applied to remove the global motion of the video frame. Considering the blocks in one frame have different motion vectors, the global motion of each block is separately estimated. Then, a neighbor-based background modeling is applied to extract the moving objects.… More >

  • Open Access

    ARTICLE

    Patient-Specific Modeling in Urogynecology: A Meshfree Approach

    J.B. Alford1, D.C. Simkins1, R.A. Rembert1, L. Hoyte, MD2

    CMES-Computer Modeling in Engineering & Sciences, Vol.98, No.2, pp. 129-149, 2014, DOI:10.3970/cmes.2014.098.129

    Abstract Mechanical deformation of tissues in the female pelvic floor is believed to be central to understanding a number of important aspects of women’s health, particularly pelvic floor dysfunction. A 2008 study of US women reported the prevalence of pelvic floor disorders in the 20 and 39 years range as 9.7% with the prevalence increasing with age until it reaches roughly 50% in the 80 and older age group [Nygaard, Barber, Burgio, and et al (2008)]. Clinical observation indicates a strong correlation between problems such as pelvic organ prolapse/urinary incontinence and vaginal childbirth. It is thought that childbirth parameters like fetal… More >

  • Open Access

    ARTICLE

    Image Segmentation Method for Complex Vehicle Lights Based on Adaptive Significance Level Set

    Jia Dongyao1,2, Zhu Huaihua1, Ai Yanke1, Zou Shengxiong1

    CMES-Computer Modeling in Engineering & Sciences, Vol.103, No.6, pp. 411-427, 2014, DOI:10.3970/cmes.2014.103.411

    Abstract The existing study on the image segmentation methods based on the image of vehicle lights is insufficient both at home and abroad, and its segmentation efficiency and accuracy is low as well. On the basis of the analysis of the regional characteristics of vehicle lights and a level set model, an image segmentation method for complex vehicle lights based on adaptive significance level set contour model is proposed in this paper. Adaptive positioning algorithm of the significant initial contour curve based on two-dimensional convex hull is designed to obtain the initial position of evolution curve, thus the adaptive ability of… More >

  • Open Access

    ARTICLE

    Methods to Automatically Build Point Distribution Models for Objects like Hand Palms and Faces Represented in Images

    Maria João M. Vasconcelos1, João Manuel R. S. Tavares1

    CMES-Computer Modeling in Engineering & Sciences, Vol.36, No.3, pp. 213-242, 2008, DOI:10.3970/cmes.2008.036.213

    Abstract In this work we developed methods to automatically extract significant points of objects like hand palms and faces represented in images that can be used to build Point Distribution Models automatically. These models are further used to segment the modelled objects in new images, through the use of Active Shape Models or Active Appearance Models. These models showed to be efficient in the segmentation of objects, but had as drawback the fact that the labelling of the landmark points was usually manually made and consequently time consuming. Thus, in this paper we describe some methods capable to extract significant points… More >

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