Human Ear Image Recognition Method Using PCA and Fisherface Complementary Double Feature Extraction  

作　　者：Yang Wang Ke Cheng Shenghui Zhao Xu E 

机构地区：[1]School of Computer and Information Engineering,Chuzhou University,Chuzhou 239000,Anhui,China [2]School of Computer,Jiangsu University of Science and Technology,Zhenjiang 212000,Jiangsu,China [3]School of Information Science and Technology,Bohai University,Jinzhou 121013,Liaoning,China

出　　处：《Journal of Artificial Intelligence and Technology》2023年第1期18-24,共7页人工智能技术学报（英文）

基　　金：National Key R&D Program of China(No:2019YFD0901605).

摘　　要：Ear recognition is a new kind of biometric identification technology now.Feature extraction is a key step in pattern recognition technology,which determines the accuracy of classification results.The method of single feature extraction can achieve high recognition rate under certain conditions,but the use of double feature extraction can overcome the limitation of single feature extraction.In order to improve the accuracy of classification results,this paper proposes a new method,that is,the method of complementary double feature extraction based on Principal Component Analysis(PCA)and Fisherface,and we apply it to human ear image recognition.The experiment was carried out on the ear image library provided by the University of Science and Technology Beijing.The results show that the ear recognition rate of the proposed method is significantly higher than the single feature extraction using PCA,Fisherface,or Independent component analysis(ICA)alone.

关 键 词：PCA ICA single feature extraction double feature extraction ear recognition 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]