N. Jayashree^1,*, R. S. Bhuvaneswaran¹

CMC-Computers, Materials & Continua, Vol.58, No.1, pp. 263-285, 2019, DOI:10.32604/cmc.2019.03924

Abstract Watermarking is a widely used solution to the problems of authentication and copyright protection of digital media especially for images, videos, and audio data. Chaos is one of the emerging techniques adopted in image watermarking schemes due to its intrinsic cryptographic properties. This paper proposes a new chaotic hybrid watermarking method combining Discrete Wavelet Transform (DWT), Z-transform (ZT) and Bidiagonal Singular Value Decomposition (BSVD). The original image is decomposed into 3-level DWT, and then, ZT is applied on the HH3 and HL3 sub-bands. The watermark image is encrypted using Arnold Cat Map. BSVD for the watermark and transformed original image… More >

Xintao Duan^1,*, Haoxian Song¹, Chuan Qin², Muhammad Khurram Khan³

CMC-Computers, Materials & Continua, Vol.55, No.3, pp. 483-493, 2018, DOI: 10.3970/cmc.2018.01798

Abstract In this paper, we propose a novel coverless image steganographic scheme based on a generative model. In our scheme, the secret image is first fed to the generative model database, to generate a meaning-normal and independent image different from the secret image. The generated image is then transmitted to the receiver and fed to the generative model database to generate another image visually the same as the secret image. Thus, we only need to transmit the meaning-normal image which is not related to the secret image, and we can achieve the same effect as the transmission of the secret image.… More >

Ya Tu¹, Yun Lin¹, Jin Wang^2,3,*, Jeong-Uk Kim⁴

CMC-Computers, Materials & Continua, Vol.55, No.2, pp. 243-254, 2018, DOI:10.3970/cmc.2018.01755

Abstract Deep Learning (DL) is such a powerful tool that we have seen tremendous success in areas such as Computer Vision, Speech Recognition, and Natural Language Pro-cessing. Since Automated Modulation Classification (AMC) is an important part in Cognitive Radio Networks, we try to explore its potential in solving signal modula-tion recognition problem. It cannot be overlooked that DL model is a complex mod-el, thus making them prone to over-fitting. DL model requires many training data to combat with over-fitting, but adding high quality labels to training data manually is not always cheap and accessible, especially in real-time system, which may counter… More >

P. PattunnaRajam^{1, *}, Reeba korah², G. Maria Kalavathy³

CMC-Computers, Materials & Continua, Vol.54, No.3, pp. 251-268, 2018, DOI:10.3970/cmc.2018.054.251

Abstract This paper presents an automated POCOFAN-POFRAME algorithm that partitions large combinational digital VLSI circuits for pseudo exhaustive testing. In this paper, a simulation framework and partitioning technique are presented to guide VLSI circuits to work under with fewer test vectors in order to reduce testing time and to develop VLSI circuit designs. This framework utilizes two methods of partitioning Primary Output Cone Fanout Partitioning (POCOFAN) and POFRAME partitioning to determine number of test vectors in the circuit. The key role of partitioning is to identify reconvergent fanout branch pairs and the optimal value of primary input node N and fanout… More >

N. Ma^1,2, K. Sato³, K. Takada⁴

CMC-Computers, Materials & Continua, Vol.46, No.3, pp. 195-219, 2015, DOI:10.3970/cmc.2015.046.195

Abstract The local mechanical behaviors of advanced high strength steels undergoing a very large strain from uniform plastic deformation to fracture were investigated with the aid of a measured displacement field and a measurement based FEM. As a measurement method, a digital image grid method (DIGM) was developed and the three-direction transient displacement field on uniaxial tensile test pieces was measured. Combining the measured transient displacement field with the finite element method, a measurement based FEM (M-FEM) was developed for the computation of distribution of the local strains, local stresses and ductile damage accumulation in a tensile test piece. Furthermore, the… More >

Ang Li¹, Guo-jian Shao^1,2, Pei-rong Du³, Sheng-yong Ding¹, Jing-bo Su⁴

CMC-Computers, Materials & Continua, Vol.45, No.1, pp. 17-38, 2015, DOI:10.3970/cmc.2015.045.017

Abstract This paper investigates the failure behaviors of stratified rocks under uniaxial compression using a digital image processing (DIP) based finite difference method (FDM). The two-dimensional (2D) mesostructure of stratified rocks, represented as the internal spatial distribution of two main rock materials (marble and greenschist), is first identified with the DIP technique. And then the binaryzation image information is used to generate the finite difference grid. Finally, the failure behaviors of stratified rock samples are simulated by FDM considering the inhomogeneity of rock materials. In the DIP, an image segmentation algorithm based on seeded region growing (SRG) is proposed, instead of… More >

Bin Li¹, Guo-biao Yang¹, Qi-rong Zhu², Fan Ni²

CMC-Computers, Materials & Continua, Vol.21, No.2, pp. 107-118, 2011, DOI:10.3970/cmc.2011.021.107

Abstract In this paper, digital image correlation method (DICM) is employed to measure the shear behavior of the spot welding specimens and the ones using adhesive under quasi-static lap shear testing. The images of the specimens' surfaces are captured in real-time by CCD and corresponding computer system. DICM is subsequently used to obtained strain by correlating the images captured before and after deformation. Then, both force-displacement curves and stress-strain curves of the specimens including the cracking load are obtained. The results and analysis show that the mechanical properties of specimens using adhesive compared with the spot welding specimens have an obvious… More >

Stephen R. Niezgoda¹, Surya R. Kalidindi^1,2

CMC-Computers, Materials & Continua, Vol.14, No.2, pp. 79-98, 2009, DOI:10.3970/cmc.2009.014.079

Abstract The generalized Hough transform is a common technique for feature detection in image processing. In this paper, we develop a size invariant Hough framework for the detection of arbitrary shapes in three dimensional digital microstructure datasets. The Hough transform is efficiently implemented via kernel convolution with complex Hough filters, where shape is captured in the magnitude of the filter and scale in the complex phase. In this paper, we further generalize the concept of a Hough filter by encoding other parameters of interest (e.g. orientation of plate or fiber constituents) in the complex phase, broadening the applicability of Hough transform… More >