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Research on Fast Face RecognitionAlgorithm Based on Block CS-LBP and HIK Kernel Method
Shaoming Pan,Gongkun Luo,Baozhong Ke,Kejiang Li 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.12
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. At the 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. For feature extraction, the authors put forward an improved CS-LBP texture feature; for feature 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. Experimental results 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. In the 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.
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