dc.contributor.author |
Nbri, Riham |
|
dc.contributor.author |
Rekrouk, Maroua |
|
dc.contributor.other |
Hamami, Latifa, Directeur de thèse |
|
dc.date.accessioned |
2023-10-09T10:28:46Z |
|
dc.date.available |
2023-10-09T10:28:46Z |
|
dc.date.issued |
2023 |
|
dc.identifier.other |
EP00540 |
|
dc.identifier.uri |
http://repository.enp.edu.dz/jspui/handle/123456789/10784 |
|
dc.description |
Mémoire de Projet de Fin d’Études : Electronique : Alger, École Nationale Polytechnique : 2023 |
fr_FR |
dc.description.abstract |
Due to the distinct and consistent traits found in the human iris, iris recognition systems have garnered significant attention for biometric identification and authentication purposes. This project presents an extensive investigation and practical implementation on FPGA of an iris recognition system, with the primary objective of creating a biometric authentication solution that is both efficient and dependable.The study conducted in this project makes notable contributions to the field of iris recognition. It introduces an innovative approach that not only improves system performance but also tackles critical challenges associated with the technology. The proposed system holds promising potential for diverse applications, including access control, surveillance, and identity verification.The valuable insights obtained from this project are expected to drive future advancements in iris recognition technology. Additionally, they play a crucial role in the ongoing development of more secure and trustworthy biometric authentication systems. |
fr_FR |
dc.language.iso |
en |
fr_FR |
dc.subject |
FPGA |
fr_FR |
dc.subject |
Iris recognition systems |
fr_FR |
dc.subject |
Biometric authentication |
fr_FR |
dc.title |
Study and implementation on FPGA of human recognition system via iris based on deep learning |
fr_FR |
dc.type |
Thesis |
fr_FR |