Face recognition technology development with Gabor, PCA and SVM methodology under illumination normalization condition
© 2017 Springer Science+Business Media New York Face recognition is a challenging research field in computer sciences, numerous studies have been proposed by many researchers. However, there have been no effective solutions reported for full illumination variation of face images in the facial recogn...
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th-cmuir.6653943832-570982018-09-05T03:35:02Z Face recognition technology development with Gabor, PCA and SVM methodology under illumination normalization condition Meijing Li Xiuming Yu Keun Ho Ryu Sanghyuk Lee Nipon Theera-Umpon Computer Science © 2017 Springer Science+Business Media New York Face recognition is a challenging research field in computer sciences, numerous studies have been proposed by many researchers. However, there have been no effective solutions reported for full illumination variation of face images in the facial recognition research field. In this paper, we propose a methodology to solve the problem of full illumination variation by the combination of histogram equalization (HE) and Gaussian low-pass filter (GLPF). In order to process illumination normalization, feature extraction is applied with consideration of both Gabor wavelet and principal component analysis methods. Next, a Support Vector Machine classifier is used for face classification. In the experiments, illustration performance was compared with our proposed approach and the conventional approaches with three different kinds of face databases. Experimental results show that our proposed illumination normalization approach (HE_GLPF) performs better than the conventional illumination normalization approaches, in face images with the full illumination variation problem. 2018-09-05T03:35:02Z 2018-09-05T03:35:02Z 2017-03-09 Journal 15737543 13867857 2-s2.0-85014726824 10.1007/s10586-017-0806-7 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85014726824&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/57098 |
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Computer Science Meijing Li Xiuming Yu Keun Ho Ryu Sanghyuk Lee Nipon Theera-Umpon Face recognition technology development with Gabor, PCA and SVM methodology under illumination normalization condition |
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© 2017 Springer Science+Business Media New York Face recognition is a challenging research field in computer sciences, numerous studies have been proposed by many researchers. However, there have been no effective solutions reported for full illumination variation of face images in the facial recognition research field. In this paper, we propose a methodology to solve the problem of full illumination variation by the combination of histogram equalization (HE) and Gaussian low-pass filter (GLPF). In order to process illumination normalization, feature extraction is applied with consideration of both Gabor wavelet and principal component analysis methods. Next, a Support Vector Machine classifier is used for face classification. In the experiments, illustration performance was compared with our proposed approach and the conventional approaches with three different kinds of face databases. Experimental results show that our proposed illumination normalization approach (HE_GLPF) performs better than the conventional illumination normalization approaches, in face images with the full illumination variation problem. |
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Journal |
author |
Meijing Li Xiuming Yu Keun Ho Ryu Sanghyuk Lee Nipon Theera-Umpon |
author_facet |
Meijing Li Xiuming Yu Keun Ho Ryu Sanghyuk Lee Nipon Theera-Umpon |
author_sort |
Meijing Li |
title |
Face recognition technology development with Gabor, PCA and SVM methodology under illumination normalization condition |
title_short |
Face recognition technology development with Gabor, PCA and SVM methodology under illumination normalization condition |
title_full |
Face recognition technology development with Gabor, PCA and SVM methodology under illumination normalization condition |
title_fullStr |
Face recognition technology development with Gabor, PCA and SVM methodology under illumination normalization condition |
title_full_unstemmed |
Face recognition technology development with Gabor, PCA and SVM methodology under illumination normalization condition |
title_sort |
face recognition technology development with gabor, pca and svm methodology under illumination normalization condition |
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2018 |
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https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85014726824&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/57098 |
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