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  • Open Access


    Enhanced Detection of Cerebral Atherosclerosis Using Hybrid Algorithm of Image Segmentation

    Shakunthala Masi*, Helenprabha Kuttiappan

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 733-744, 2023, DOI:10.32604/iasc.2023.025919

    Abstract In medical science for envisaging human body’s phenomenal structure a major part has been driven by image processing techniques. Major objective of this work is to detect of cerebral atherosclerosis for image segmentation application. Detection of some abnormal structures in human body has become a difficult task to complete with some simple images. For expounding and distinguishing neural architecture of human brain in an effective manner, MRI (Magnetic Resonance Imaging) is one of the most suitable and significant technique. Here we work on detection of Cerebral Atherosclerosis from MRI images of patients. Cerebral Atherosclerosis is a cerebral vascular disease causes… More >

  • Open Access


    Implicit Continuous User Authentication for Mobile Devices based on Deep Reinforcement Learning

    Christy James Jose1,*, M. S. Rajasree2

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1357-1372, 2023, DOI:10.32604/csse.2023.025672

    Abstract The predominant method for smart phone accessing is confined to methods directing the authentication by means of Point-of-Entry that heavily depend on physiological biometrics like, fingerprint or face. Implicit continuous authentication initiating to be loftier to conventional authentication mechanisms by continuously confirming users’ identities on continuing basis and mark the instant at which an illegitimate hacker grasps dominance of the session. However, divergent issues remain unaddressed. This research aims to investigate the power of Deep Reinforcement Learning technique to implicit continuous authentication for mobile devices using a method called, Gaussian Weighted Cauchy Kriging-based Continuous Czekanowski’s (GWCK-CC). First, a Gaussian Weighted… More >

  • Open Access


    Blood Group Classification System Based on Image Processing Techniques

    S. A. Shaban*, D. L. Elsheweikh

    Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 817-834, 2022, DOI:10.32604/iasc.2022.019500

    Abstract The present paper proposes a novel system that automatically classifies the eight different blood groups according to the ABO and Rh blood group systems. The proposed system is developed by applying MATLAB’s image processing techniques on the blood sample images. These images are acquired from the laboratory using the slide test. It utilizes a mean filter for removing noise from blood sample images. In addition, the Contrast Limited Adaptive Histogram Equalization (CLAHE) is used for enhancing the image characteristics analysis. The proposed system also utilizes the automated threshold strategy (Otsu’s approach) for obtaining the blood samples binary images. Since, adding… More >

  • Open Access


    An Enhanced Nonlocal Self-Similarity Technique for Fabric Defect Detection

    Boheng Wang1, Li Ma1, Jielin Jiang1,2,*

    Journal of Information Hiding and Privacy Protection, Vol.1, No.3, pp. 135-142, 2019, DOI:10.32604/jihpp.2019.07432

    Abstract Fabric defect detection has been an indispensable and important link in fabric production, many studies on the development of vision based automated inspection techniques have been reported. The main drawback of existing methods is that they can only inspect a particular type of fabric pattern in controlled environment. Recently, nonlocal self-similarity (NSS) based method is used for fabric defect detection. This method achieves good defect detection performance for small defects with uneven illumination, the disadvantage of NNS based method is poor for detecting linear defects. Based on this reason, we improve NSS based defect detection method by introducing a gray… More >

  • Open Access


    Frequency Domain Filtering SAR Interferometric Phase Noise Using the Amended Matrix Pencil Model

    Y,ong Gao1, Shubi Zhang1,*, Kefei Zhang2,*, Shijin Li1

    CMES-Computer Modeling in Engineering & Sciences, Vol.119, No.2, pp. 349-363, 2019, DOI:10.32604/cmes.2019.03943

    Abstract Interferometric phase filtering is one of the key steps in interferometric synthetic aperture radar (InSAR/SAR). However, the ideal filtering results are difficult to obtain due to dense fringe and low coherence regions. Moreover, the InSAR/SAR data range is relatively large, so the efficiency of interferential phase filtering is one of the major problems. In this letter, we proposed an interferometric phase filtering method based on an amended matrix pencil and linear window mean filter. The combination of the matrix pencil and the linear mean filter are introduced to the interferometric phase filtering for the first time. First, the interferometric signal… More >

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