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dc.contributor.author Adjabi, Insaf
dc.contributor.author Benzaoui, Amir
dc.date.accessioned 2025-05-26T09:34:18Z
dc.date.available 2025-05-26T09:34:18Z
dc.date.issued 2024-10-25
dc.identifier.issn issn
dc.identifier.uri http://depot.umc.edu.dz/handle/123456789/14648
dc.description.abstract Biometric authentication, such as fingerprints and facial recognition, is increasingly used for securing devices and networks but still poses security risks. Palmprints offer a promising alternative. In this work, we introduce a new feature extraction method, Triangular and Orthogonal Local Binary Patterns (TAO-LBP), based on the LBP descriptor. TAO-LBP improves orientation and texture coding, enhancing robustness to rotation and orientation changes. Experiments on IITD and CASIA palmprint datasets show that TAO-LBP outperforms standard LBP, making it a more reliable method for palmprint recognition. fr_FR
dc.language.iso en fr_FR
dc.publisher Université Frères Mentouri - Constantine 1 fr_FR
dc.title TAO-LBP: A Novel Approach for Palmprint-Based Biometric Authentication fr_FR
dc.type Presentation fr_FR


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