casa 24(1):

Research Article

Advancements in Iris Recognition: WAHET-CNN Framework for Accurate Segmentation and Pattern Classification

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  • @ARTICLE{10.4108/eetcasa.v9i1.3708,
        author={Nguyen Kim Quoc and Ha Minh Tan and Dang Nhu Phu and Vuong Xuan Chi and Phan Cong Vinh},
        title={Advancements in Iris Recognition: WAHET-CNN Framework for Accurate Segmentation and Pattern Classification},
        journal={EAI Endorsed Transactions on Context-aware Systems and Applications},
        volume={9},
        number={1},
        publisher={EAI},
        journal_a={CASA},
        year={2023},
        month={8},
        keywords={iris recognition, periocular recognition, iris segmentation, iris biometric, personal identification},
        doi={10.4108/eetcasa.v9i1.3708}
    }
    
  • Nguyen Kim Quoc
    Ha Minh Tan
    Dang Nhu Phu
    Vuong Xuan Chi
    Phan Cong Vinh
    Year: 2023
    Advancements in Iris Recognition: WAHET-CNN Framework for Accurate Segmentation and Pattern Classification
    CASA
    EAI
    DOI: 10.4108/eetcasa.v9i1.3708
Nguyen Kim Quoc1,*, Ha Minh Tan1, Dang Nhu Phu1, Vuong Xuan Chi1, Phan Cong Vinh1
  • 1: Trường ĐH Nguyễn Tất Thành
*Contact email: nkquoc@ntt.edu.vn

Abstract

Biometric and identification patterns have gained extensive research and application, particularly in iris recognition. The iris harbors a wealth of individual-specific information, making it a vital element in biometric authentication. This article presents a comprehensive study encompassing iris segmentation and identification. We introduce the Weighted Adaptive Hough Ellipsopolar Transform Convolutional Neural Network (WAHET-CNN) as a novel approach for classifying pattern images. Our experimental outcomes demonstrate a commendable 90% accuracy achieved by the proposed WAHET-CNN on the CASIA dataset Version 4.