DocumentCode
3500925
Title
Face Recognition Based on the Phase Spectrum of Local Normalized Image
Author
Olivares-Mercado, Jesus ; Hotta, Kazuhiro ; Takahashi, Haruhisa ; Perez-Meana, Hector ; Sanchez-Perez, Gabriel
fYear
2008
fDate
27-31 Oct. 2008
Firstpage
123
Lastpage
127
Abstract
This paper proposes a robust faces recognition method based on the phase spectrum features of the local normalized image. The principal components analysis (PCA) and the support vector machine (SVM) are used in the classification stage. We evaluate how the proposed method is robust to illumination, occlusion and expressions using "AR face database", which includes the face images of 109 subjects (60 males and 49 females) under illumination changes, expression changes and partial occlusion. The proposed method provides results with a correct recognition rate more than 95.5%.
Keywords
face recognition; feature extraction; image classification; principal component analysis; support vector machines; visual databases; PCA; SVM; face recognition; local normalized image; partial occlusion; phase spectrum; phase spectrum features; principal components analysis; support vector machine; Biometrics; Character recognition; Data mining; Face recognition; Image recognition; Lighting; Principal component analysis; Robustness; Support vector machine classification; Support vector machines; Face Recognition; Local Normalized Image; PCA; Phase Spectrum; SVM;
fLanguage
English
Publisher
ieee
Conference_Titel
Artificial Intelligence, 2008. MICAI '08. Seventh Mexican International Conference on
Conference_Location
Atizapan de Zaragoza
Print_ISBN
978-0-7695-3441-1
Type
conf
DOI
10.1109/MICAI.2008.46
Filename
4682453
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