关键词: 虹膜识别, 人眼定位, 轻量级网络, 广义交并比

Abstract:

In view of the current human eye localization algorithm to deal with the complex environment of the anti-interference ability is not strong, the positioning accuracy is poor and there is no left and right eye classification, an algorithm for human eye location and left and right eye classification of iris image based on lightweight network is proposed. The EL-YOLO model is designed by using YOLO algorithm combined with the high-performance lightweight network model. The Generalized Intersection-over-Union（GIoU） is introduced into the loss function, which enables the network training to converge quickly and achieve high positioning accuracy. The experimental results on the datasets CASIA-IrisV4, MIR2016, and the datasets SEPAD_V1 and SEPAD_V2 collected by our lab show that the EL-YOLO model is small, runs fast, has a high accuracy of positioning and classification, and has a strong generalization ability.

Key words: iris recognition, human eye location, lightweight network, generalized intersection-over-union