虹膜识别技术的应用与发展

虹膜识别技术是一种生物特征识别技术,本文在分析其研究现状、识别流程的基础上,简单的介绍了虹膜图像的采集、虹膜定位、归一化与增强、虹膜编码、比较与判决等主要内容。     

Efficient iris recognition via ICA feature and SVM classifier

With the increasing demands of security in ournet worked society,the technology for personalidentification works as the main solution to safe-guard people s properties.Biometrics is an alterna-tive to solve the problemand has the advantage thatthey cannot be stolen or forgotten like pass words.Because personal identification numbers or identifi-cation tokens(such as s mart cards)cannot provide ahighlevel of security which can be copied,inspec-ted and/or stolen.They only showthe knowledgeof som…     

迎接生物识别时代

高科技手段使鉴别人的身份越来越容易 所谓生物特征识别,是指通过计算机将人体所固有的生理特征或行为特征收集并进行处理,来进行个人身份鉴定的技术.生理特征与生俱来,多为先天性的;行为特征则是习惯使然,多为后天形成.科学家将生理和行为特征统称为生物特征,常见的生物特征包括指纹、掌纹、虹膜、脸像、声音、笔迹等.     

Eye and Iris Detection Using Projection and Radial Symmetry Transform

This paper presents an eye and iris detection algorithm for human facial images. The authors combine three features of the eye to develop the algorithm: 1) the pixels surrounding the eyes are more variable than other parts of the face; 2) eye pixels are darker than their neighbors; 3) eyes often exhibit radial symmetric properties. Through the first feature, two rough regions of both eyes are detected on the face. Eye masks are then formed based on the second feature, and a fast radial symmetry transform is applied to the two rough regions of both eyes. Finally, accurate iris centers are located by searching the maximum value of the radial symmetry transform results. Using 450 human facial images from the Caltech face database, experiments show that the success rate of the proposed method is 91.7%. The effectiveness of the method was also verified through detection of video frames.     

先天性虹膜囊肿3例报告

本文报告了3例先天性虹膜囊肿,其中1例系双眼多发性,继发青光眼,在高眼压下成功的进行了手术切除,并对虹膜囊肿的分类,发病机理,治疗等进行了讨论。     

New Iris Localization Method Based on Chaos Genetic Algorithm

This paper present a new method based on Chaos Genetic Algorithm (CGA) to localize the human iris in a given image. First, the iris image is preprocessed to estimate the range of the iris localization, and then CGA is used to extract the boundary of the iris. Simulation results show that the proposed algorithms is efficient and robust, and can achieve sub pixel precision. Because Genetic Algorithms (GAs) can search in a large space, the algorithm does not need accurate estimation of iris center for subsequent localization, and hence can lower the requirement for original iris image processing. On this point, the present localization algirithm is superior to Daugman‘s algorithm.     

基于图象灰度的虹膜定位算法

讨论了基于图象灰度的虹膜定位算法,并提出了基于灰度的虹膜外边界提取、模式匹配的相关算法.实验证明了该算法的有效性.