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  • Open Access

    ARTICLE

    A Robust Zero-Watermarking Based on SIFT-DCT for Medical Images in the Encrypted Domain

    Jialing Liu1, Jingbing Li1,2,*, Yenwei Chen3, Xiangxi Zou1, Jieren Cheng1,2, Yanlin Liu1, Uzair Aslam Bhatti1,2

    CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 363-378, 2019, DOI:10.32604/cmc.2019.06037

    Abstract Remote medical diagnosis can be realized by using the Internet, but when transmitting medical images of patients through the Internet, personal information of patients may be leaked. Aim at the security of medical information system and the protection of medical images, a novel robust zero-watermarking based on SIFT-DCT (Scale Invariant Feature Transform-Discrete Cosine Transform) for medical images in the encrypted domain is proposed. Firstly, the original medical image is encrypted in transform domain based on Logistic chaotic sequence to enhance the concealment of original medical images. Then, the SIFT-DCT is used to extract the feature sequences of encrypted medical images.… More >

  • Open Access

    ARTICLE

    Text Detection and Recognition for Natural Scene Images Using Deep Convolutional Neural Networks

    Xianyu Wu1, Chao Luo1, Qian Zhang2, Jiliu Zhou1, Hao Yang1, 3, *, Yulian Li1

    CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 289-300, 2019, DOI:10.32604/cmc.2019.05990

    Abstract Words are the most indispensable information in human life. It is very important to analyze and understand the meaning of words. Compared with the general visual elements, the text conveys rich and high-level moral information, which enables the computer to better understand the semantic content of the text. With the rapid development of computer technology, great achievements have been made in text information detection and recognition. However, when dealing with text characters in natural scene images, there are still some limitations in the detection and recognition of natural scene images. Because natural scene image has more interference and complexity than… More >

  • Open Access

    ARTICLE

    A Method of Obtaining Catchment Basins with Contour Lines for Foam Image Segmentation

    Yanpeng Wu1, Xiaoqi Peng1,*, Mohammad Nur2, Hengfu Yang1

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1155-1170, 2019, DOI:10.32604/cmc.2019.06123

    Abstract Foam image segmentation, represented by watershed algorithm, is wildly used in the extraction of bubble morphology features. H-minima transformation was proved to be effective in locating the catchment basins in the traditional watershed segmentation method. To further improve the accuracy of watershed segmentation, method of top-bottom-cap filters and method of morphological reconstruction were implied to marking the catchment basins. In this paper, instead of H-minima transformation, a method of contour lines is specially proposed to obtain the catchment basins for foam image segmentation by using top-bottom-cap filters and less morphological reconstruction. Experimental results in foam segmentation show that the proposed… More >

  • Open Access

    ARTICLE

    An Efficient Crossing-Line Crowd Counting Algorithm with Two-Stage Detection

    Zhenqiu Xiao1,*, Bin Yang2, Desy Tjahjadi3

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1141-1154, 2019, DOI:10.32604/cmc.2019.05638

    Abstract Crowd counting is a challenging task in crowded scenes due to heavy occlusions, appearance variations and perspective distortions. Current crowd counting methods typically operate on an image patch level with overlaps, then sum over the patches to get the final count. In this paper we describe a real-time pedestrian counting framework based on a two-stage human detection algorithm. Existing works with overhead cameras is mainly based on visual tracking, and their robustness is rather limited. On the other hand, some works, which focus on improving the performances, are too complicated to be realistic. By adopting a line sampling process, a… More >

  • Open Access

    ARTICLE

    Satellite Cloud-Derived Wind Inversion Algorithm Using GPU

    Lili He1,2, Hongtao Bai1,2, Dantong Ouyang1,2, Changshuai Wang1,2, Chong Wang1,2,3, Yu Jiang1,2,*

    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 599-613, 2019, DOI:10.32604/cmc.2019.05928

    Abstract Cloud-derived wind refers to the wind field data product reversely derived through satellite remote sensing cloud images. Satellite cloud-derived wind inversion has the characteristics of large scale, computationally intensive and long time. The most widely used cloud-derived serial--tracer cloud tracking method is the maximum cross-correlation coefficient (MCC) method. In order to overcome the efficiency bottleneck of the cloud-derived serial MCC algorithm, we proposed a parallel cloud-derived wind inversion algorithm based on GPU framework in this paper, according to the characteristics of independence between each wind vector calculation. In this algorithm, each iteration is considered as a thread of GPU cores,… More >

  • Open Access

    ARTICLE

    Adaptive Median Filtering Algorithm Based on Divide and Conquer and Its Application in CAPTCHA Recognition

    Wentao Ma1, Jiaohua Qin1,*, Xuyu Xiang1, Yun Tan1, Yuanjing Luo1, Neal N. Xiong2

    CMC-Computers, Materials & Continua, Vol.58, No.3, pp. 665-677, 2019, DOI:10.32604/cmc.2019.05683

    Abstract As the first barrier to protect cyberspace, the CAPTCHA has made significant contributions to maintaining Internet security and preventing malicious attacks. By researching the CAPTCHA, we can find its vulnerability and improve the security of CAPTCHA. Recently, many studies have shown that improving the image preprocessing effect of the CAPTCHA, which can achieve a better recognition rate by the state-of-the-art machine learning algorithms. There are many kinds of noise and distortion in the CAPTCHA images of this experiment. We propose an adaptive median filtering algorithm based on divide and conquer in this paper. Firstly, the filtering window data quickly sorted… More >

  • Open Access

    ARTICLE

    R2N: A Novel Deep Learning Architecture for Rain Removal from Single Image

    Yecai Guo1,2,*, Chen Li1,2, Qi Liu3

    CMC-Computers, Materials & Continua, Vol.58, No.3, pp. 829-843, 2019, DOI:10.32604/cmc.2019.03729

    Abstract Visual degradation of captured images caused by rainy streaks under rainy weather can adversely affect the performance of many open-air vision systems. Hence, it is necessary to address the problem of eliminating rain streaks from the individual rainy image. In this work, a deep convolution neural network (CNN) based method is introduced, called Rain-Removal Net (R2N), to solve the single image de-raining issue. Firstly, we decomposed the rainy image into its high-frequency detail layer and low-frequency base layer. Then, we used the high-frequency detail layer to input the carefully designed CNN architecture to learn the mapping between it and its… More >

  • Open Access

    ARTICLE

    An Improved Unsupervised Image Segmentation Method Based on Multi-Objective Particle Swarm Optimization Clustering Algorithm

    Zhe Liu1,2,*, Bao Xiang1,3, Yuqing Song1, Hu Lu1, Qingfeng Liu1

    CMC-Computers, Materials & Continua, Vol.58, No.2, pp. 451-461, 2019, DOI:10.32604/cmc.2019.04069

    Abstract Most image segmentation methods based on clustering algorithms use single-objective function to implement image segmentation. To avoid the defect, this paper proposes a new image segmentation method based on a multi-objective particle swarm optimization (PSO) clustering algorithm. This unsupervised algorithm not only offers a new similarity computing approach based on electromagnetic forces, but also obtains the proper number of clusters which is determined by scale-space theory. It is experimentally demonstrated that the applicability and effectiveness of the proposed multi-objective PSO clustering algorithm. More >

  • Open Access

    ARTICLE

    A Weighted Threshold Secret Sharing Scheme for Remote Sensing Images Based on Chinese Remainder Theorem

    Qi He1, Shui Yu2, Huifang Xu3,*, Jia Liu4, Dongmei Huang5, Guohua Liu6, Fangqin Xu3, Yanling Du1

    CMC-Computers, Materials & Continua, Vol.58, No.2, pp. 349-361, 2019, DOI:10.32604/cmc.2019.03703

    Abstract The recent advances in remote sensing and computer techniques give birth to the explosive growth of remote sensing images. The emergence of cloud storage has brought new opportunities for storage and management of massive remote sensing images with its large storage space, cost savings. However, the openness of cloud brings challenges for image data security. In this paper, we propose a weighted image sharing scheme to ensure the security of remote sensing in cloud environment, which takes the weights of participants (i.e., cloud service providers) into consideration. An extended Mignotte sequence is constructed according to the weights of participants, and… More >

  • Open Access

    ARTICLE

    A Robust Image Watermarking Scheme Using Z-Transform, Discrete Wavelet Transform and Bidiagonal Singular Value Decomposition

    N. Jayashree1,*, 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 >

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