Ethnic Features Extraction and Recognition of Human Faces

摘要：

Ethnic Facial Feature is one of tbe most important face features. We create a face database of ethnic groups and extract facial features by using face recognition technology. In tbe feature extraction method, we adapt the algebra and geometry features from face database. In algebra features, LDA algorithm extracting tbe algebraic features of human face images is used. Tbe paper also constructs a new face template to extract the geometric features and locates the points of face templates by using Gabor Wavelet KNN and C5.0 Classifiers are used to learn the train dataset. The result indicates that the average recognition accuracy rates of Tibetan, Uighur and Zhuang ethnic groups can reach 79％ by algebraic features and 90.95％ by geometry features.

关键词： Minority characters of face Face recognition LDA PCA Gabor Wavelet Minority recognition

作者: DUAN Xiao-dong WANG Cun-rui LIU Xiang-dong LI Zhi-jie WU Jun ZHANG Hai-long

作者单位: The Research Institute of Nonlinear Information Technology of Dalian Nationalities University,Dalian The Research Institute of Nonlinear Information Technology of Dalian Nationalities University,Dalian The Graduate School, Northeastern University, Shenyang CHINA ,110004

会议类型: 国际会议

会议名称: The 2nd IEEE International Conference on Advanced Computer Control(第二届先进计算机控制国际会议 ICACC 2010)

会议地点: 沈阳

会议语种:英文

页码: 125-130

在线出版日期: 2010-03-27（万方平台首次上网日期，不代表论文的发表时间）