Abstract
This paper proposes a robust faces recognition method based on the Normalization and the Phase Spectrum of the Local Part of an 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 96.7%.
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Olivares-Mercado, J., Hotta, K., Takahashi, H., Perez-Meana, H., Miyatake, M.N., Sanchez-Perez, G. (2008). Face Recognition Based on Normalization and the Phase Spectrum of the Local Part of an Image. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2008. Lecture Notes in Computer Science, vol 5359. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89646-3_27
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DOI: https://doi.org/10.1007/978-3-540-89646-3_27
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-89645-6
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