一种基于局部信息统计的虹膜分块编码方法

由于虹膜自身的稳定性、非侵犯性、不可更改性等优点,虹膜识别已经成为生物特征身份鉴别领域中的研究热点。但虹膜丰富的纹理和复杂的结构给特征提取和编码带来了很大困难。为尽可能地简化特征提取和编码方法,提高虹膜识别效率,提出了一种基于局部信息统计的虹膜分块编码方法。对原始人眼图像进行虹膜定位等预处理操作,得到归一化的虹膜纹理图像;分别根据虹膜局部信息与全局信息、局部信息与局部信息之间的比较关系进行分块编码;计算了不同虹膜代码之间的汉明(Hamming)距离。根据汉明距离给出识别结果。实验证明该方法有效、可行,具有较高的识别率和识别速度。

An Iris Block-Encoding Method Based on Statistic of Local Information

Thanks to many advantages of the iris,such as stable,nonintrusive,and unchangeable,iris recognition has been a research hot-subject in the biometrics identification field.However,the abundant textures and complex structures of irises lead to a great number of troubles for feature extraction and encoding.In order to simplify the feature extraction and encoding method and improve the efficiency of iris recognition,an iris block-encoding method based on statistic of local information is proposed.Firstly,it achieves preprocessing of the original eye image,such as iris localization,and gets the normalized iris features image.Secondly,according to the comparative relationships between local information and global information,local information and local information,it accomplishes the iris block-encoding.Thirdly,it calculates the Hamming distance between different iris codes and obtains the recognition result according to Hamming distance.Experimental results demonstrated that the proposed method is effective and feasible.It also has high recognition accuracy and speed.