期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2016
卷号：9
期号：12
页码：207
出版社：SERSC
摘要：With the development of artificial intelligence and pattern recognition technology, more and more research related to human face is constantly developing in all walks of life. Atthe present stage, the traditional face recognition algorithm based on LBP and SVM is not good, and the process of feature extraction and feature classification are deeply studied in this paper. Forfeature extraction, the authors put forward an improved CS-LBP texture feature; forfeature classification, the author uses the histogram intersection (HIK) kernel function to classify the features which has high efficiency and good effect. Subsequently, experiments are carried out on the Yale data set and the ORL data set. Experimentalresults show that the proposed algorithm has a significant improvement on the face recognition effect of face direction change, and the illumination change is slightly improved. Inthe natural environment, most face recognition has the influence of human face direction and noise, and the effect of noise is a hot direction of face recognition research in the future.
