A Novel Efficient Classwise Sparse and Collaborative Representation for Holistic Palmprint Recognition
المؤلف | Rida I. |
المؤلف | Al Maadeed N. |
المؤلف | Al Maadeed S. |
تاريخ الإتاحة | 2019-11-03T11:47:38Z |
تاريخ النشر | 2018 |
اسم المنشور | 2018 NASA/ESA Conference on Adaptive Hardware and Systems, AHS 2018 |
المصدر | Scopus |
الملخص | Palmprint recognition is an important and widely used modality in biometric systems. It has a high reliability, stability and user acceptability. Although the discriminative ability of the existing state-of-the-art holistic techniques, their effectiveness heavily relies upon the quality of training data. Indeed, palmprint images contain different information including identity, illumination and distortions related to the acquisition systems. To overcome this problem, we explore a novel efficient holistic Classwise Sparse and Collaborative Representation (CSR). Extensive experiments have been performed on two existing and widely used palmprint datasets: multispectral and Poly U. The obtained experimental results demonstrated very encouraging performances when compared to state-of-the-art techniques. � 2018 IEEE. |
راعي المشروع | This publication was made possible using a grant from the Qatar National Research Fund through National Priority Research Program (NPRP) No. 8-140-2-065. The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the Qatar National Research Fund or Qatar University. |
اللغة | en |
الناشر | Institute of Electrical and Electronics Engineers Inc. |
الموضوع | biometrics holistic palmprint security |
النوع | Conference Paper |
الصفحات | 156 - 161 |
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