Open AccessResearch on Image Preprocessing Algorithm and Deep Learning of Iris Recognition
Author(s) -
Weibin Zhou,
MA Xiao-tong,
Yong Zhang
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1621/1/012008
Subject(s) - iris recognition , biometrics , artificial intelligence , iris (biosensor) , computer science , segmentation , preprocessor , pattern recognition (psychology) , hough transform , edge detection , enhanced data rates for gsm evolution , computer vision , deep learning , image (mathematics) , image processing
With the development of information society, biometrics technology has been paid more and more attention. Iris recognition is considered as the most promising biometric authentication technology in the 21st century because of its uniqueness, stability and non-creativity. However, due to the high cost of iris recognition equipment and some defects of the algorithm, iris recognition cannot be applied in real life on a large scale. In this paper, a fast localization iris recognition algorithm is proposed, which combines the iris segmentation algorithm with deep learning to quickly extract the iris region for recognition. Firstly, the pupil edge was extracted by dynamic threshold analysis and contour extraction, and then iris was located by edge detection and gray calculation. Finally, features of normalized images were learned by deep learning network. Experiments show that the method can guarantee the accuracy and efficiency of iris segmentation and has a high degree of recognition and matching.