%0 Journal Article
%T Feature extraction and recognition of iris based on ICA-MJE and SVM<br>基于ICA-MJE和SVM的虹膜特征提取与识别
%A HE Zhen-hong
%A Lü Lin-tao
%A <br>何振红
%A 吕林涛
%J 计算机应用
%D 2007
%I 
%X A new method for iris feature extraction and recognition was proposed in this paper. Feature was extracted with independent component analysis by maximizing J-divergence entropy (ICA-MJE), and then Support Vector Machine (SVM) was used to match two iris codes. Compared with that of Gabor wavelet method, the size of an iris code and the processing time of the feature extraction were significantly reduced. Experimental results show that the developed system with high iris recognition rate could be used for a personal identification system in a more efficient and effective manner.
%K iris recognition
%K feature extraction
%K independent component analysis
%K Support Vector Machine
%K J-divergence entropy<br>虹膜识别
%K 特征提取
%K 独立分量分析
%K 支持向量机
%K 判别熵
%K 虹膜纹理
%K 特征提取
%K 识别系统
%K based
%K iris
%K recognition
%K extraction
%K 身份
%K 应用
%K 识别率
%K 算法
%K 结果
%K 实验
%K 改进
%K 编码时间
%K 编码长度
%K 比较
%K 识别方法
%K 小波
%K Gabor
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=14E16CBD27430512D51C5C627193A0E6&yid=A732AF04DDA03BB3&vid=DB817633AA4F79B9&iid=B31275AF3241DB2D&sid=CAF3E71A6764366D&eid=5D9E227628843A85&journal_id=1001-9081&journal_name=计算机应用&referenced_num=0&reference_num=8