Ethnic Features extraction and recognition of human faces

Ethnic Facial Feature is one of the most important face features. We create a face database of ethnic groups and extract facial features by using face recognition technology. In the feature extraction method, we adapt the algebra and geometry features from face database. In algebra features, LDA algorithm extracting the algebraic features of human face images is used. The 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.