Abstract
In this paper, we propose a modified face authentication method based on the image preprocessing (histogram equalization, HE) and with SURF algorithm (Speeded Up Robust Features) in the feature extraction step. In particular, our methodology aims at determining a person’s authenticity when he/she has a few facial expressions, different backgrounds or a variance in lighting. We evaluated the performance of this method using public face databases like The Extended Cohn-Kanade Dataset (CK+) and Caltech Faces. We made some test using sixty images (thirty per database), Equal (E) or Different (D) and according to the match between images (for example Image 1 and Image 2) and a defined threshold, our method determines if a person is authenticated or not. The results showed that with the database CK+ was obtained 93% and with Caltech Faces 86% of accuracy in the authentication process, these results were compared with those obtained by some algorithms like LDA, PCA, SIFT and SURF (without preprocessing) and we can conclude that the authentication rate was improved.
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Mendoza-Martinez, C., Pedraza-Ortega, J.C., Ramos-Arreguin, J.M. (2014). A Novel Approach for Face Authentication Using Speeded Up Robust Features Algorithm. In: Gelbukh, A., Espinoza, F.C., Galicia-Haro, S.N. (eds) Human-Inspired Computing and Its Applications. MICAI 2014. Lecture Notes in Computer Science(), vol 8856. Springer, Cham. https://doi.org/10.1007/978-3-319-13647-9_33
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DOI: https://doi.org/10.1007/978-3-319-13647-9_33
Publisher Name: Springer, Cham
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