基于经验模态分解的虹膜识别  

Iris Recognition Based on Empirical Mode Decomposition

作　　者：韩民[1] 彭玉华[1] 张顺利[1] 孙伟峰[1] 

机构地区：[1]山东大学信息科学与工程学院,山东济南250100

出　　处：《光学学报》2010年第2期364-368,共5页Acta Optica Sinica

基　　金：国家自然科学基金(30870666)资助课题

摘　　要：虹膜识别是一种有效的生物特征识别方法。经验模态分解(EMD)是一种可自适应的对非线性、非平稳信号进行多分辨率分解的信号分析算法。将虹膜图像进行EMD分解,找出有利于虹膜识别的敏感频带,使用选择后的固有模态分量对虹膜图像进行特征提取。仿真实验结果表明,该方法正确识别率达到99.44%,并且由于其在特征提取的同时消除了高频噪声和背景光影响,简化了预处理过程,降低了算法的复杂度。Iris recognition is an effective method of biometrics recognition. Empirical mode decomposition（EMD）,a multi-resolution decomposition technique,is adaptive and appears to be suitable for nonlinear,non-stationary data analysis. We adopt the EMD approach to decompose the iris images and select the intrinsic mode functions with proper frequency range for iris recognition. The experimental results indicate that the recognition rate can achieve 99.44%; meanwhile,the complexity of the algorithm can be reduced because the effect of high frequency noise and illumination can be eliminated during our feature extraction process.

关 键 词：生物光学 生物特征识别 虹膜识别 经验模态分解 固有模态函数 特征提取 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]