文章基本信息

标题：Algorithm for Iris recognition based on contourlet Transform and Entropy
本地全文：下载
作者：Ayoub Ezzaki ; Nadia Idrissi ; Francisco-Angel Moreno 等
期刊名称：ELCVIA: electronic letters on computer vision and image analysis
印刷版ISSN：1577-5097
出版年度：2020
卷号：19
期号：1
页码：53-68
DOI：10.5565/rev/elcvia.1190
出版社：Centre de Visió per Computador
摘要：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.
关键词：Iris;Biometric;Segmentation;Hough transform;contourlet Transform;entropy