Iris recognition algorithm based on Contourlet Transform and Entropy

Scopus: 5 cites, Google Scholar: cites

Iris recognition algorithm based on Contourlet Transform and Entropy
Ezzaki, Ayoub (Mohammed V University in Rabat. Physics Department)
Idrissi, Nadia (Mohammed V University in Rabat. Physics Department)
Moreno Dueñas, Francisco Ángel (Universidad de Málaga. Departamento de Ingeniería de Sistemas y Automática)
Masmoudi, Lhoussaine (Mohammed V University in Rabat. Physics Department)

Data:	2020
Resum:	The iris is one of the most secure biometric information that is widely employed in authentication systems. In this paper we present a method for iris recognition based on the Contourlet Transform and Entropy which entails i) the detection and segmentation of the iris, ii) its normalization, iii) the application of the Contourlet Transform, iv) the generation of the iris descriptor, and v) the matching between the query iris and those in the database. The proposed method has been tested with images taken from the popular CASIA-V4 and UBIRIS. v1 datasets and compared against four other iris recognition algorithms. The results show a higher true positive rate with a reduced computation time.
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Matèria:	Iris ; Biometric ; Contourlet Transform ; Entropy ; Segmentation ; Hough transform
Publicat a:	ELCVIA. Electronic letters on computer vision and image analysis, Vol. 19 Núm. 1 (2020) , p. 53-67 (Regular Issue) , ISSN 1577-5097

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Registre creat el 2020-07-31, darrera modificació el 2025-01-11