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  • Open Access

    ARTICLE

    Skin Lesion Classification System Using Shearlets

    S. Mohan Kumar*, T. Kumanan

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 833-844, 2023, DOI:10.32604/csse.2023.022385

    Abstract The main cause of skin cancer is the ultraviolet radiation of the sun. It spreads quickly to other body parts. Thus, early diagnosis is required to decrease the mortality rate due to skin cancer. In this study, an automatic system for Skin Lesion Classification (SLC) using Non-Subsampled Shearlet Transform (NSST) based energy features and Support Vector Machine (SVM) classifier is proposed. At first, the NSST is used for the decomposition of input skin lesion images with different directions like 2, 4, 8 and 16. From the NSST’s sub-bands, energy features are extracted and stored in the feature database for training.… More >

  • Open Access

    ARTICLE

    Automatic Segmentation of Liver from Abdominal Computed Tomography Images Using Energy Feature

    Prabakaran Rajamanickam1, Shiloah Elizabeth Darmanayagam1,*, Sunil Retmin Raj Cyril Raj2

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 709-722, 2021, DOI:10.32604/cmc.2021.014347

    Abstract Liver Segmentation is one of the challenging tasks in detecting and classifying liver tumors from Computed Tomography (CT) images. The segmentation of hepatic organ is more intricate task, owing to the fact that it possesses a sizeable quantum of vascularization. This paper proposes an algorithm for automatic seed point selection using energy feature for use in level set algorithm for segmentation of liver region in CT scans. The effectiveness of the method can be determined when used in a model to classify the liver CT images as tumorous or not. This involves segmentation of the region of interest (ROI) from… More >

  • Open Access

    ARTICLE

    An Efficient Detection Approach of Content Aware Image Resizing

    Ming Lu1, 2, *, Shaozhang Niu1, Zhenguang Gao3

    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 887-907, 2020, DOI:10.32604/cmc.2020.09770

    Abstract Content aware image resizing (CAIR) is an excellent technology used widely for image retarget. It can also be used to tamper with images and bring the trust crisis of image content to the public. Once an image is processed by CAIR, the correlation of local neighborhood pixels will be destructive. Although local binary patterns (LBP) can effectively describe the local texture, it however cannot describe the magnitude information of local neighborhood pixels and is also vulnerable to noise. Therefore, to deal with the detection of CAIR, a novel forensic method based on improved local ternary patterns (ILTP) feature and gradient… More >

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