針對(duì)人耳圖像自身的特點(diǎn)，并通過(guò)對(duì)現(xiàn)有生物識(shí)別技術(shù)的研究，本文嘗試采用了一種
基于核函數(shù)的Fisher 判別分析算法對(duì)人耳進(jìn)行識(shí)別。該算法不僅可以有效地提取人耳特征，獲得較高的識(shí)別率；而且還可以解決因?yàn)楣庹蘸腿硕D(zhuǎn)角度等因素帶來(lái)的非線性問(wèn)題。實(shí)驗(yàn)表明: 采用基于徑向基核函數(shù)的Fisher 判別分析算法對(duì)人耳圖像進(jìn)行識(shí)別，其識(shí)別率最
高，為98.701%。
關(guān)鍵詞： 人耳識(shí)別，特征提取，F(xiàn)isher 判別分析算法，核函數(shù)
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，F(xiàn)DA algorithm，kernel function