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
Link To Document :
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