Publication Type:

Journal Article

Source:

Proceedings of the International Conference on Soft Computing Systems, Advances in Intelligent Systems and Computing, Springer Verlag, Volume 397, p.501-509 (2016)

ISBN:

9788132226697

URL:

http://www.scopus.com/inward/record.url?eid=2-s2.0-84955266830&partnerID=40&md5=480c8e4244af2e81eaa693baa1dbdab2

Keywords:

Biometric authentication, Biometrics, Cross validation, Face images, Face recognition, Feature extraction, Gabor filters, Gabor wavelets, Orientation analysis, Soft computing, Support vector machines, Texture analysis, Useful properties

Abstract:

Gabor filters have achieved enormous success in texture analysis, feature extraction, segmentation, iris and face recognition. Face recognition is one of the most popular biometric modalities which has wide range of applications in biometric authentication. The most useful property of a Gabor filter is that it can achieve multi-resolution and multi-orientation analysis of an image. This paper presents an algorithm using Gabor wavelets in capturing discriminatory content, obtained by convolving a face image with coefficients of Gabor filter with different orientations and scales. Support vector machine (SVM) has been used to construct a robust classifier. This method has been tested with publicly available ORL dataset. This algorithm has been tested, cross-validated and the detailed results are presented. It is inferred that the proposed method offers a recognition rate (94%) with tenfold cross-validation. © Springer India 2016.

Notes:

cited By 0; Conference of International Conference on Soft Computing Systems, ICSCS 2015 ; Conference Date: 20 April 2015 Through 21 April 2015; Conference Code:160689

Cite this Research Publication

R. Karthika, Parameswaran Latha, B.K., P., and L.P., S., “Study of Gabor wavelet for face recognition invariant to pose and orientation”, Proceedings of the International Conference on Soft Computing Systems, Advances in Intelligent Systems and Computing, vol. 397, pp. 501-509, 2016.