基于核函数的Fisher判别分析算法在人耳识别中的应用

针对人耳图像自身的特点，并通过对现有生物识别技术的研究，本文尝试采用了一种
基于核函数的Fisher 判别分析算法对人耳进行识别。该算法不仅可以有效地提取人耳特征，获得较高的识别率；而且还可以解决因为光照和人耳旋转角度等因素带来的非线性问题。实验表明: 采用基于径向基核函数的Fisher 判别分析算法对人耳图像进行识别，其识别率最
高，为98.701%。
关键词： 人耳识别，特征提取，Fisher 判别分析算法，核函数
Application of Kernel Function Based Fisher Discriminant Analysis Algorithm in
Ear Recognition LIU Ying, MU Zhi-chun, YUAN Li (School of Information Engineering, University of Science and Technology Beijing, Beijing 100083) Abstract: According to the characteristic of ear image and the study of the existing biometricsrecognition technology, we try to use a Fisher discriminant analysis algorithm based on kernel function for ear recognition in this paper. The algorithm can not only extract ear feature effectively and achieve a high recognition rate, but also resolve the nonlinear issue caused by lighting variation and pose variation etc. The experiment shows that it achieves the highest recognition rate of 98.701% when using Fisher discriminant analysis algorithm based on RBF kernel function to recognize the ear image.
Key words: ear recognition，feature extraction，FDA algorithm，kernel function