A novel approach for face authentication using Speeded Up Robust Features algorithm

被引:2
作者
Universidad Autonoma de Queretaro, Queretaro, Mexico [1 ]
机构
[1] Universidad Autonoma de Queretaro, Queretaro
来源
Lect. Notes Comput. Sci. | / 356-367期
关键词
Biometrics; Computer vision; Face authentication; Image processing; OpenCV; !text type='Python']Python[!/text; SURF;
D O I
10.1007/978-3-319-13647-9_33
中图分类号
学科分类号
摘要
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. © Springer International Publishing Switzerland 2014.
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页码:356 / 367
页数:11
相关论文
共 17 条
[1]  
Brumnik R., Podbregar I., Ivanusa T., Reliability of Fingerprint Biometry (Weibull Approach), Biometric Systems, Design and Applications, pp. 3-4, (2011)
[2]  
Yang J., Poh N., Recent Application in Biometrics, (2011)
[3]  
Kremic E., Subasi A., The Implementation of Face Security for Authentication Implemented on Mobile Phone, The International Arab Journal of Information Technology, (2011)
[4]  
Lu X., Image Analysis for Face Recognition, (2003)
[5]  
Lowe D.G., Distinctive image features from scale-invariant keypoints, International Journal of Computer Vision, 60, 2, pp. 91-110, (2004)
[6]  
Bay H., Tuytelaars T., Van Gool L., SURF: Speeded up robust features, ECCV 2006, Part I. LNCS, 3951, pp. 404-417, (2006)
[7]  
Oyallon E., Rabin J., An analysis and implementation of the SURF method, and its comparison to SIFT, Image Processing on Line, (2013)
[8]  
Boullosa O., Estudio comparativo de descriptores visuales para la detección de escenas cuasi-duplicadas (Comparativestudy of visual descriptorsfordetectingnearduplicatescenes), (2011)
[9]  
Lucey P., Cohn J.F., Kanade T., Saragih J., Ambadar Z., Matthews I., The Extended Cohn-Kanade Dataset (CK+): A complete expression dataset for action unit and emotionspecified expression, Proceedings of the Third International Workshop on CVPR for Human Communicative Behavior Analysis (CVPR4HB 2010), pp. 94-101, (2010)
[10]  
Weber M., Unsupervised Learning of Models for Object Recognition, (2000)