人脸正面图像中眼睛的精确定位  

Precisely Locating Human Eyes from Front-View Face Images

作　　者：宋加涛[1] 刘济林[1] 池哲儒[2] 王蔚[3] 

机构地区：[1]浙江大学信息与通信工程研究所,杭州310027 [2]香港理工大学电子及资讯工程系多媒体信号处理中心 [3]宁波工程学院电子技术系,宁波315016

出　　处：《计算机辅助设计与图形学学报》2005年第3期540-545,共6页Journal of Computer-Aided Design & Computer Graphics

基　　金：浙江省自然科学基金 (60 2 118);宁波市青年基金 (0 2J2 0 12 0 0 2 )

摘　　要：提出了人脸图像中眼睛定位方法 ,首先对灰度图像进行灰度形态学操作 ,所得谷图中像素数总体上随灰度级的增加而显著减少 ;用位于高端的灰度值作为阈值 ,逐次对谷图进行二值化 ,从所得二值图像中获得眼睛的候选位置 ;用PCA方法进行眼睛位置的最佳选择 该方法解决了二值化阈值步长的自适应选取问题 用AR ,Yale和自建人脸数据库进行实验 ,得到眼睛定位成功率大于 93% ,平均定位偏差小于眼球半径的 1In this paper, a novel method for automatic localization of human eyes from front-view face images is presented. By applying the grayscale morphology operation to a face image, we can obtain a valley map with a good property in which as a whole the number of pixels at a grayscale decreases significantly as the grayscale level increases. The valley map is then binarized with a set of threshold values determined adaptively, and several candidate eye locations are detected from the resultant binary images. The final eye positions are determined using a Principle Component Analysis (PCA) method. Experimental results on the AR, Yale and our own face image databases show that the correct eye location rate is over 93% and the location disparity on average is below 1?3 of the radius of an eye ball.

关 键 词：眼睛定位 人脸图像处理 灰度数学形态学 谷图 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]