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dc.contributor.authorCHELAOUA, RACHID-
dc.contributor.authorFEHDI, OUSSAMA-
dc.contributor.authorBENABDALLAH, MOHAMED-
dc.date.accessioned2024-10-02T09:16:18Z-
dc.date.available2024-10-02T09:16:18Z-
dc.date.issued2024-
dc.identifier.citationFACULTY OF NEW TECHNOLOGIES OF INFORMATION AND COMMUNICATIONen_US
dc.identifier.urihttps://dspace.univ-ouargla.dz/jspui/handle/123456789/37020-
dc.descriptionTelecommunications Systemsen_US
dc.description.abstractPalm print recognition is physiological biometric method used for recognition of per- son. It consists of various features like texture, statistical, geometry features. Which are used separately or by the combination of two or more features for quick and correct recognition purpose. This technology is beneficial in various fields such as security, access control to buildings, secure payment applications. In this thesis, presents the proposed biometric system, where the deep learning AlexNet is applied on palm-print recognition biometric system. Thus, we based on 2D-DWT as image fusion method and explain their structures. For more comprehen- sive evaluation, we changed parameters and variable of our neural network to selected best combination. Based on the results, excellent accuracy rates war achieved, that provide an overview of the performance of the proposed recognition system.en_US
dc.description.sponsorshipDepartment of Electronic and Telecommunicationsen_US
dc.language.isoenen_US
dc.publisherUNIVERSITY OF KASDI MERBAH OUARGLAen_US
dc.subjectPALMPRINTen_US
dc.subjectALEXNETen_US
dc.subject2D-DWTen_US
dc.subjectFEATURE FUSIONen_US
dc.titleBiometric Images Processing and Recognitionen_US
dc.typeThesisen_US
Appears in Collections:Département d'Electronique et des Télécommunications - Master

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