Cross-Age Face Recognition Based on HOG/PCA/SVM

doi:10.13438/j.cnki.jdzk.2018.05.006

Abstract

Abstract:

To realize face recognition of different age groups,gradient magnitude and gradient direction are used to measure the image similarity.Firstly,face images from database FG-NET are preprocessed.The HOG algorithm is used to extract the feature values,and then the PCA method is used to reduce the feature values.Finally,the samples are input into the SVM for training,and the face recognition is matched.The matching degree is up to 90.91%.The experimental results verify the effectiveness of the algorithm.

Key words: face recognition, image preprocessing, histogram of oriented gradient, principal component analysis, support vector machine

PENG Sijiang,DAI Houping,ZHOU Chengfu,LIU Qian. Cross-Age Face Recognition Based on HOG/PCA/SVM[J]. Journal of Jishou University（Natural Sciences Edition), DOI: 10.13438/j.cnki.jdzk.2018.05.006.

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Cross-Age Face Recognition Based on HOG/PCA/SVM

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