Research on face recognition technology based on KPCA and SVM under convolutional filtering

Anbang Wang; Wentao Zhao

doi:10.1117/12.2600352

1 June 2021 Research on face recognition technology based on KPCA and SVM under convolutional filtering

Anbang Wang, Wentao Zhao

Proceedings Volume 11848, International Conference on Signal Image Processing and Communication (ICSIPC 2021); 118480O (2021) https://doi.org/10.1117/12.2600352
Event: International Conference on Signal Image Processing and Communication (ICSIPC 2021), 2021, Chengdu, China

Abstract

Face recognition is an important and difficult problem in the field of artificial intelligence and image vision. This paper studies the feature face principal component analysis (PCA) based on statistical features, which is used to reduce the gray dimension of face image extraction. Aiming at the problem that PCA can't handle the nonlinear reduction of face image information and the classification of prediction results well, the multi-classification voting algorithm of KPCA and SVM is adopted. Due to the limitations of the feature face technology, the feature extraction of the local sensitive area of the face is insufficient. The convolutional filter is designed to preprocess the image to enhance the extraction of the contour features of the face and the feature of the key area. Experimental results show that this method can improve the recognition accuracy.

Citation Download Citation

Anbang Wang and Wentao Zhao "Research on face recognition technology based on KPCA and SVM under convolutional filtering", Proc. SPIE 11848, International Conference on Signal Image Processing and Communication (ICSIPC 2021), 118480O (1 June 2021); https://doi.org/10.1117/12.2600352

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