虹膜识别算法的研究

虹膜识别是一种非常可靠的身份鉴别方法.在讨论虹膜图像定位、增强等预处理方法的基础上,针对现有虹膜识别算法中存在的问题,提出了虹膜有效区域选择、特征提取及编码匹配的有效方法.在虹膜图像有效区域的选择上,根据虹膜图像自身的生物特点采用一种新的分割方法,使得到的图像纹理信息更充足;在图像的特征提取方面,采用Gabor小波变换,将频率分为2个频段,不同的频段选择不同Gabor尺度参数,并选择适当的位置参数;为解决虹膜图像的旋转对虹膜识别的影响,将获得的虹膜编码进行错位匹配.实验结果表明,所提出的虹膜识别算法效果较好.

Research on the algorithms of iris recognition

Iris recognition is a very reliable method for personal identity verification.To improve upon conventional algorithms related to iris recognition,methods are proposed for available region selection,texture feature extraction,and code matching of the iris.On the selection of available regions,a new division method was applied according to the biometric feature of the iris itself to obtain more information.In the area of texture feature extraction,the transforms of a Gabor wavelet are introduced.Dividing the frequencies of Gabor into two bands,different Gabor scale parameters were selected in every band,and the appropriate location parameters were chosen.Finally,in order to resolve the effects of iris image rotation on the overall result of iris recognition,it was found that the binary iris codes achieved must be compared using a method of shifting in a fixed length.Experimental results show that the proposed iris recognition methods perform better than conventional methods.