关键词: 虹膜识别, 人眼定位, 方向梯度直方图（HOG）, 级联支持向量机（SVM）分类器, 图像预处理

Abstract: Aiming at the problems such as low accuracy and poor generalization ability of the existing human eye location algorithms under near infrared light, a human eye location algorithm based on Histogram Oriented Gradient（HOG） and Support Vector Machine（SVM） is proposed. HOG is used to extract the human eye features of iris images and the HOG features are trained by SVM classifier to locate human eyes. In order to further improve the accuracy and reduce the missing detection and false detection, a multi-level cascade SVM classifier algorithm is proposed. In addition, aiming at the unique grayscale distribution characteristics of iris images under near infrared light, an image preprocessing method is designed, which can significantly improve the positioning speed. The experimental results on MIR2016 and CASIA-IRIS-Distance dataset show that the human eye location algorithm based on HOG and SVM has high accuracy, strong generalization ability and high real-time performance.

Key words: iris recognition, eye location, Histogram Oriented Gradient（HOG）, cascade Support Vector Machine（SVM）, image preprocessing