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基于特征加权融合的虹膜识别算法 预览

Iris recognition algorithm based on feature weighted fusion
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摘要 由于单一虹膜特征相对简单,容易引起虹膜识别不准确的问题,本文使用特征加权融合来表示虹膜纹理。提取虹膜纹理的空域特征和频域特证,使用主成分分析法(PCA)降噪去冗余。空域特征采用二分统计局部二值模式(DS-LBP)表示虹膜纹理的灰度值变化规律,形成空域特征码。频域特征采用二维Haar小波提取虹膜纹理的高频系数,形成频域特征码。分别计算两个特征码的汉明(Hamming)距离,并乘以相应的加权权重。通过与设定的分类阈值比较来判定虹膜类别。用多种虹膜库与其他虹膜识别算法进行比较,实验结果表明,本文算法在识别率、等错率、稳定性等方面更具有优势。 The features of single iris are relatively simple,which can easily lead to the inaccurate iris recognition.To solve this problem,the feature weighted fusion is used to represent the iris texture in this paper.First,the iris texture spatial domain features and frequency domain features are extracted using Principal Component Analysis(PCA)to reduce noise and redundancy.Second,Dichotomous Statistical Local Binary Pattern(DSLB)is used to represent variation rule of iris texture gray value,forming spatial domain feature code;and for frequency domain features,2 D-Haar wavelet is used to extract the high frequency coefficients of iris feature and form frequency domain feature code.Third,the Hamming distances of the two feature codes are calculated respectively and multiplied by the corresponding weighted factors.Finally,the iris category is determined by comparison with the setclassification threshold.A variety of iris libraries are used to compare the performance of proposed algorithm with other iris recognition algorithms.Experiment results show that the proposed algorithm has more advantages in recognition rate,equal error rate and stability.
作者 刘元宁 刘帅 朱晓冬 刘天慧 杨霞 LIU Yuan-ning;LIU Shuai;ZHU Xiao-dong;LIU Tian-hui;Yang Xia(Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education,Jilin University,Changchun 130012,China;College of Computer Science and Technology,Jilin University,Changchun 130012,China;College of Software,Jilin University,Changchun 130012,China;Electronic Information Products Supervision Inspection Institute of Jilin Province,Changchun 130021,China)
出处 《吉林大学学报:工学版》 EI CAS CSCD 北大核心 2019年第1期221-229,共9页 Journal of Jilin University:Eng and Technol Ed
基金 国家自然科学基金项目(61471181) 吉林省自然科学基金项目(20140101194JC,20150101056JC).
关键词 人工智能 特征加权融合 主成分分析法 二分统计局部二值模式 二维Haar小波 汉明距离 artificial intelligence feature weighted fusion principal component analysis(PCA) dichotomous statistical local binary pattern 2D-Haar wavelet Hamming distance
作者简介 刘元宁(1962-),男,教授,博士生导师.研究方向:虹膜识别.E-mail:lyn@jlu.edu.cn;通信作者:朱晓冬(1964-),男,教授,博士生导师.研究方向:虹膜识别.E-mail:zhuxd@jlu.edu.cn.
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