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Edited by: Editorial Board of Journal of Data Acquisition and Processing
P.O. Box 2704, Beijing 100190, P.R. China
Sponsored by: Institute of Computing Technology, CAS & China Computer Federation
Undertaken by: Institute of Computing Technology, CAS
Published by: SCIENCE PRESS, BEIJING, CHINA
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      07 April 2023, Volume 38 Issue 2   
    Article

    COMPRESSED CONTOUR CUMULATIVE GLCM TEXTURE ANALYSIS MODEL BASED CNN FOR PALMPRINT RECOGNITION SYSTEM
    Abirami B1, Krishnaveni K2
    Journal of Data Acquisition and Processing, 2023, 38 (2): 923-941 . 

    Abstract

    In this research paper, Compressed Contour Cumulative GLCM Texture Analysis Model based CNN for Palmprint Recognition (3CGLCM-CNNNet) System is proposed to make up the higher level security assurance in the biometric technology. It can be imparted by second-order statistics using a Cumulative Gray-Scale Level Co-occurrence Matrix (CGLCM) feature extraction approach and Convolution Neural Network (CNNNet) classification approach. To enact this, Two Dimensional-Palmprint Region of Interest (2D-PROI) is pre-processed and contour of 2D-PROI image (CP) is captured using canny edge detection algorithm. Linear Hybrid Conventional Compression Algorithm (LHCC) is applied to constitute the compressed contour 2D-PROI (CCPI) image. In this LHCC algorithm, conventional Discrete Wavelet Transform (DWT) and Principal Component Analysis (PCA) compression algorithms is composited in a linear manner on CP. Ideal second-order statistical texture features of CCPI are clipped using CGLCM approach. Ideal features are forwarded into 3CGLCM-CNNNet classification algorithm to match the recognized persons. Research is worked on 2D-PROI data derived from the POLYU database, Hong Kong Polytechnic University, Hong Kong. Our proposed system’s benchmark has been evaluated and tabulated with higher acceptance of 99% recognition accuracy compared with other existing approaches in biometric technology.

    Keyword

    Biometric Technology, Palmprint Biometric Trait, Gray-Scale Level Co-occurrence Matrix, Convolution Neural Network, Two Dimensional-Palmprint, Region of Interest, Canny edge detection, District Wavelet Transform, Principal Component analysis, Statistic texture features.


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ISSN 1004-9037

         

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