Compare Gabor Fisher Classifier and Phase-Based Gabor Fisher Classifier for Face Recognition
Journal of Electrical and Electronic Engineering
Volume 1, Issue 2, June 2013, Pages: 41-45
Received: May 11, 2013;
Published: Jun. 10, 2013
Views 2857 Downloads 220
Nouar Larbi, Department of Electronique, University of Sidi Bel Abbes 22000, Algeria
Dine Mohamed, College of Engineering, Djillali Liabes University, Sidi-Bel-Abbes 22000, Algeria
The paper compares two feature extraction techniques for face recognition with Gabor Filters. Firstly Gabor Filters based methods which mainly use only Gabor magnitude features like Gabor Fisher Classifier (GFC), and secondly the proposed method called the Phase-based Gabor Fisher Classifier (PBGFC) by turk. The PBGFC method constructs an augmented feature vector which encompasses Gabor-phase information derived from a novel representation of face images - the oriented Gabor phase congruency image (OGPCI) - and then applies linear discriminant analysis to the augmented feature vector to reduce its dimensionality. In ours experiments we use the ORL data base, the feasibility of the proposed methods was assessed in a series of face verification experiments. The experimental results show that the PBGFC method performs better than other popular feature extraction techniques such as (LDA), while it ensures nearly similar verification performance as the established Gabor Fisher Classifier (GFC).
Compare Gabor Fisher Classifier and Phase-Based Gabor Fisher Classifier for Face Recognition, Journal of Electrical and Electronic Engineering.
Vol. 1, No. 2,
2013, pp. 41-45.
C. Liu, "Capitalize on dimensionality increasing techniques for improving face recognition grand challenge performance," IEEE Transactions on Image Processing, vol. 11, no. 4, pp. 467–476,2002.
J. Short, J. Kittler, and K. Messer, "Photometric normalisation for face verification," in Proceedings of the 5th AVBPA, New York, USA, July 2005, pp. 617–626.
V. ˇStruc, and N. Paveˇsi´c, The Complete Gabor-Fisher Classifier for Robust Face Recognition, EURASIP Advances in Signal Processing, vol. 2010, 26 pages, doi:10.1155/2010/847680, 2010.
C. Liu and H. Wechsler, "Gabor feature based classification using the enhanced fisher linear discriminant model for face recognition," IEEE
L. Shen, L. Bai, and M. Fairhurst, "Gabor wavelets and general discriminant analysis for face identification and verification," Image and Vision Computing, vol. 25, no. 5, pp. 553–563, 2007.
M. Lades, J. Vorbruggen, J. Buhmann, J. Lange, C. von der Malsburg, R. Wurtz, and W. Konen, "Distortion invariant object recognition in the dynamic link architectrue," IEEE Transactions on Computers, vol. 42, no. 3, pp. 300–311, 1993.
L. Shen and L. Bai, "A review of Gabor wavelets for face recognition," Pattern Analysis and Applications, vol. 9, no. 2,pp.273-292,2006.
V. Kyrki, J.-K. Kamarainen, and H. K¨alvi¨ainen, "SimpleGabor feature space for invariant object recognition," Pattern Recognition Letters, vol. 25, no. 3, pp. 311–318, 2004.
L. Shen and L. Bai, "Information theory for Gabor feature selection for face recognition," EURASIP Journal on Applied Signal Processing, vol. 2006, Article ID 30274, 11 pages, 2006.
B. Zhang, S. Shan, X. Chen, and W. Gao, "Histogram of gabor phase patterns (hgpp): A novel object representation approach for face recognition," IEEE Transactions on Image Processing, vol. 16, no. 1, pp. 57–68, 2007.
B. Kovesi, "Image features from phase congruency," Videre: Journal of Computer Vision Research, vol. 1, no. 3, pp. 1–26, 1999.
V. ˇ Struc and N. Paveˇsi´c, "A palmprint verification system based on phase congruency feautres," in Proceedings of the COST 2101 Workshop on Biometrics and Identity Manegement(BIOID’08), Denmark, May 2008.
P. Belhumeur, J. Hespanha, and D. Kriegman, "Eigenfaces vs. fisherfaces: Recognition using class specific linear projection," in Proceedings of the 4th ECCV, Cambridge, UK, April 1996, pp. 45–58.
V. ˇ Struc, F. Miheliˇc, and N. Paveˇsi´c, "Face authentication using a hybridapproach," Journal of Electronic Imaging, vol. 17, no. 1, 2008.