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  • Open Access

    ARTICLE

    Two Stage Classification with CNN for Colorectal Cancer Detection

    Pallabi Sharma1,*, Kangkana Bora2, Kunio Kasugai3, Bunil Kumar Balabantaray1

    Oncologie, Vol.22, No.3, pp. 129-145, 2020, DOI:10.32604/oncologie.2020.013870

    Abstract In this paper, we address a current problem in medical image processing, the detection of colorectal cancer from colonoscopy videos. According to worldwide cancer statistics, colorectal cancer is one of the most common cancers. The process of screening and the removal of pre-cancerous cells from the large intestine is a crucial task to date. The traditional manual process is dependent on the expertise of the medical practitioner. In this paper, a two-stage classification is proposed to detect colorectal cancer. In the first stage, frames of colonoscopy video are extracted and are rated as significant if More >

  • Open Access

    REVIEW

    Flesh Color Diversity of Sweet Potato: An Overview of the Composition, Functions, Biosynthesis, and Gene Regulation of the Major Pigments

    Hanna Amoanimaa-Dede, Chuntao Su, Akwasi Yeboah, Chunhua Chen, Shaoxia Yang, Hongbo Zhu*, Miao Chen*

    Phyton-International Journal of Experimental Botany, Vol.89, No.4, pp. 805-833, 2020, DOI:10.32604/phyton.2020.011979 - 09 November 2020

    Abstract Sweet potato is a multifunctional root crop and a source of food with many essential nutrients and bioactive compounds. Variations in the flesh color of the diverse sweet potato varieties are attributed to the different phytochemicals and natural pigments they produce. Among them, carotenoids and anthocyanins are the main pigments known for their antioxidant properties which provide a host of health benefits, hence, regarded as a major component of the human diet. In this review, we provide an overview of the major pigments in sweet potato with much emphasis on their biosynthesis, functions, and regulatory More >

  • Open Access

    ARTICLE

    The Instance-Aware Automatic Image Colorization Based on Deep Convolutional Neural Network

    Hui Li1, Wei Zeng1,*, Guorong Xiao2, Huabin Wang1

    Intelligent Automation & Soft Computing, Vol.26, No.4, pp. 841-846, 2020, DOI:10.32604/iasc.2020.010118

    Abstract Recent progress on image colorization is substantial and benefiting mostly from the great development of the deep convolutional neural networks. However, one type of object can be colored by different kinds of colors. Due to the uncertain relationship between the object and color, the deep neural network is unstable and difficult to converge during the training process. In order to solve this problem, this paper proposes an instance-aware automatic image colorization algorithm, which uses the semantic features of the object instance as prior knowledge to guide the deep neural network to do the colorization task. More >

  • Open Access

    ARTICLE

    Application Research of Color Design and Collocation in Image Processing

    Feiying Xia1, Shenghong Huang2,*

    Computer Systems Science and Engineering, Vol.35, No.2, pp. 91-98, 2020, DOI:10.32604/csse.2020.35.098

    Abstract Color is one of the primary elements of artistic expression. Its design and collocation play a very important role in image processing. While the number of people using the Internet is increasing, more attention is being paid to the user’s experience including the color design and matching of the Internet web interface, in order to reach the color design of the web interface with image processing as the core. This thesis firstly discusses the importance of web interface color design and matching in image processing from the image processing appeal of the web interface and More >

  • Open Access

    ARTICLE

    Color Image Segmentation Using Soft Rough Fuzzy-C-Means and Local Binary Pattern

    R.V.V. Krishna1,*, S. Srinivas Kumar2

    Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 281-290, 2020, DOI:10.31209/2019.100000121

    Abstract In this paper, a color image segmentation algorithm is proposed by extracting both texture and color features and applying them to the one -against-all multi class support vector machine (MSVM) classifier for segmentation. Local Binary Pattern is used for extracting the textural features and L*a*b color model is used for obtaining the color features. The MSVM is trained using the samples obtained from a novel soft rough fuzzy c-means (SRFCM) clustering. The fuzzy set based membership functions capably handle the problem of overlapping clusters. The lower and upper approximation concepts of rough sets deal well More >

  • Open Access

    ARTICLE

    Robust Visual Tracking Models Designs Through Kernelized Correlation Filters

    Detian Huang1, Peiting Gu2, Hsuan-Ming Feng3,*, Yanming Lin1, Lixin Zheng1

    Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 313-322, 2020, DOI:10.31209/2019.100000105

    Abstract To tackle the problem of illumination sensitive, scale variation, and occlusion in the Kernelized Correlation Filters (KCF) tracker, an improved robust tracking algorithm based on KCF is proposed. Firstly, the color attribute was introduced to represent the target, and the dimension of target features was reduced adaptively to obtain low-dimensional and illumination-insensitive target features with the locally linear embedding approach. Secondly, an effective appearance model updating strategy is designed, and then the appearance model can be adaptively updated according to the Peak-to-Sidelobe Ratio value. Finally, the low-dimensional color features and the HOG features are utilized More >

  • Open Access

    ARTICLE

    Median Filtering Detection Based on Quaternion Convolutional Neural Network

    Jinwei Wang1, 2, 3, 4, Qiye Ni3, Yang Zhang3, Xiangyang Luo2, *, Yunqing Shi5, Jiangtao Zhai3, Sunil Kr Jha3

    CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 929-943, 2020, DOI:10.32604/cmc.2020.06569 - 23 July 2020

    Abstract Median filtering is a nonlinear signal processing technique and has an advantage in the field of image anti-forensics. Therefore, more attention has been paid to the forensics research of median filtering. In this paper, a median filtering forensics method based on quaternion convolutional neural network (QCNN) is proposed. The median filtering residuals (MFR) are used to preprocess the images. Then the output of MFR is expanded to four channels and used as the input of QCNN. In QCNN, quaternion convolution is designed that can better mix the information of different channels than traditional methods. The More >

  • Open Access

    ARTICLE

    Deer Body Adaptive Threshold Segmentation Algorithm Based on Color Space

    Yuheng Sun1, Ye Mu1, 2, 3, 4, *, Qin Feng5, Tianli Hu1, 2, 3, 4, He Gong1, 2, 3, 4, Shijun Li1, 2, 3, 4, Jing Zhou6

    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1317-1328, 2020, DOI:10.32604/cmc.2020.010510 - 10 June 2020

    Abstract In large-scale deer farming image analysis, K-means or maximum betweenclass variance (Otsu) algorithms can be used to distinguish the deer from the background. However, in an actual breeding environment, the barbed wire or chain-link fencing has a certain isolating effect on the deer which greatly interferes with the identification of the individual deer. Also, when the target and background grey values are similar, the multiple background targets cannot be completely separated. To better identify the posture and behaviour of deer in a deer shed, we used digital image processing to separate the deer from the… More >

  • Open Access

    ARTICLE

    Fast Single Image Haze Removal Method for Inhomogeneous Environment Using Variable Scattering Coefficient

    Rashmi Gupta1, Manju Khari1, Vipul Gupta1, Elena Verdú2, Xing Wu3, Enrique Herrera-Viedma4, Rubén González Crespo2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.123, No.3, pp. 1175-1192, 2020, DOI:10.32604/cmes.2020.010092 - 28 May 2020

    Abstract The images capture in a bad environment usually loses its fidelity and contrast. As the light rays travel towards its destination they get scattered several times due to the tiny particles of fog and pollutants in the environment, therefore the energy gets lost due to multiple scattering till it arrives its destination, and this degrades the images. So the images taken in bad weather appear in bad quality. Therefore, single image haze removal is quite a bit tough task. Significant research has been done in the haze removal algorithm but in all the techniques, the… More >

  • Open Access

    ARTICLE

    A Novel Approach of Image Steganography for Secure Communication Based on LSB Substitution Technique

    Shahid Rahman1, Fahad Masood2, Wajid Ullah Khan2, Niamat Ullah1, Fazal Qudus Khan3, Georgios Tsaramirsis3, Sadeeq Jan4, *, Majid Ashraf5

    CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 31-61, 2020, DOI:10.32604/cmc.2020.09186 - 20 May 2020

    Abstract Steganography aims to hide the messages from unauthorized persons for various purposes, e.g., military correspondence, financial transaction data. Securing the data during transmission is of utmost importance these days. The confidentiality, integrity, and availability of the data are at risk because of the emerging technologies and complexity in software applications, and therefore, there is a need to secure such systems and data. There are various methodologies to deal with security issues when utilizing an open system like the Internet. This research proposes a new technique in steganography within RGB shading space to achieve enhanced security… More >

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