基于眼底高分辨力毛细血管图像的身份识别  

Identification Recognition Based on High Resolution Retinal Capillary Vessel Image of Human Eye

作　　者：祁传琦[1] 鲍华[2,3] 杨汉生[2,3] 戴云[2] 

机构地区：[1]成都航空职业技术学院机械系,成都610021 [2]中国科学院光电技术研究所,成都610209 [3]中国科学院研究生院,北京100039

出　　处：《光电工程》2009年第9期132-136,共5页Opto-Electronic Engineering

基　　金：国家自然科学基金资助项目(60808031)

摘　　要：视网膜识别技术稳定性好,安全性高。常规眼底相机获得的图像分辨力低,给图像编码和模式匹配带来困难,使得基于常规眼底相机的视网膜身份识别技术难以推广应用。利用自适应光学眼底视网膜高分辨力成像技术采集眼底视网膜高分辨力毛细血管图像,经归一化和滤噪后,采用Gabor滤波算法进行特征提取,汉明距离进行模式匹配,对实验样本进行了准确的身份识别,验证了该技术的有效性,拓展了自适应光学眼底视网膜高分辨力成像技术的应用范围,在某些要害部门可能发挥重要的安保作用。Retina recognition has the advantages of high stability and security. Because low resolution retina image obtained by traditional fundus camera is difficult to be coded and matched, retina identification recognition is not widely applied. High resolution capillary vessel image is acquired by adaptive optics high resolution retina imaging technique, and the texture of image is extracted by Gabor filters after being normalized and denoised, The character matching is completed by Hamming distance. Experimental results show that the proposed method can accurately identify different samples and is feasible. Retina capillary vessel identification recognition extends the application of adaptive optics high resolution retina imaging technique and has a potential application in some important situation.

关 键 词：眼底图像 自适应光学 GABOR滤波器 身份识别 视网膜识别 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]