摘要
分别针对眼睑和眼睫毛遮挡噪声,利用其灰度和形状信息提出了2种灰度形态学检测算法.1)设计弧线形的形态学结构元素,经过灰度开启运算、图像分割和边缘检测,获得眼睑边缘的候选点集,再利用B啨zier曲线拟合出眼睑边缘;2)构造交叉形的形态学结构元素,通过灰度开启运算得到直方图具有分段特性的虹膜图像,经二值化检测出眼睫毛.实验结果表明:文中算法能有效地检测2种遮挡噪声,有助于降低虹膜识别系统的等错误率,提高模式的可分性.
Two gray-scale morphological algorithms are presented for the detection of eyelid and eyelash occlusions based on intensity and shape information. Firstly, an arc morphological structuring element is designed for detecting eyelid edge. A set of candidate points for eyelid edge can be obtained by gray-scale morphological opening, image segmenting, and edge detecting. Then the eyelid edge is fitted on the basis of B6zier curves. Secondly, a crossed morphological structuring element is developed. An iris image, whose intensity is mostly distributed in several sections, can be acquired after gray-scale morphological opening. Thus a binary image of eyelashes is obtained. The experimental results show that the proposed algorithms are effective on detecting these two kinds of occlusion noises, and helpful to reduce the Equal Error Rate of iris recognition system, and finally able to improve the discriminability of iris patterns.
出处
《计算机辅助设计与图形学学报》
EI
CSCD
北大核心
2007年第3期346-350,共5页
Journal of Computer-Aided Design & Computer Graphics
基金
国家自然科学基金(60472083)
关键词
虹膜识别
眼睑遮挡检测
眼睫毛遮挡检测
灰度形态学
iris recognition
eyelid occlusions detection
eyelash occlusions detection
gray-scale morphology
