| Paper title: |
Face Recognition using Gabor Filters |
| Published in: | Issue 2, (Vol. 5) / 2011 |
| Publishing date: | 2011-10-28 |
| Pages: | 53-57 |
| Author(s): | SHARIF Muhammad , KHALID Adeel , RAZA Mudassar , MOHSIN Sajjad |
| Abstract. | An Elastic Bunch Graph Map (EBGM) algorithm is being proposed in this research paper that successfully implements face recognition using Gabor filters. The proposed system applies 40 different Gabor filters on an image. As a result of which 40 images with different angles and orientation are received. Next, maximum intensity points in each filtered image are calculated and mark them as Fiducial points. The system reduces these points in accordance to distance between them. The next step is calculating the distances between the reduced points using distance formula. At last, the distances are compared with database. If match occurs, it means that the image is recognized. |
| Keywords: | Face, Recogntion, Image, Gabor, Distance Formula |
| References: | 1. D. S. Bolme. “Elastic bunch graph matching”. Master’s thesis, Colorado State University, Fort Collins, Colorado, USA, 2003, Pages 775-779 2. C. Aguerrebere, G. Capdehourat, M. Delbracio, M. Mateu, A. Fern´andez and F. Lecumberry. “An Improved Face Recognition Algorithm through Gabor Filter Adaptation” June 2007, Pages 74-79 3. B. Kepenekci, F. B. Tek, and G. B. Akar. “Occluded face recognition by using gabor features”. In 3rd COST 276 Workshop on Information and Knowledge Management for Integrated Media Communication, Budapest, October 2002. 4. W. Zhao, R. Chellappa, P. J. Phillips, and A. Rosenfeld. “Face recognition: A literature survey. ACM Computing Surveys”, 35(4): pages 399–458, 2003. 5. M. Kirby and L. Sirovich. “Application of the KarhunenLo`eve procedure for the characterization of human faces”. IEEE Transactions on Pattern Analysis and Machine Intelligence,12(1): pages 103–108, 1990. 6. M. Turk and A. P. Pentland. Eigenfaces for recognition. Journal of Cognitive Neuroscience, 3(1): pages 71–86, 1991. 7. L. Wiskott, J.-M. Fellous, N. Kr¨uger, and C. von der Malsburg. Face recognition by elastic bunch graph matching. In L. C. Jain, U. Halici, I. Hayashi, and S. B. Lee, editors, Intelligent Biometric Techniques in Fingerprint and Face Recognition, chapter 11, pages 355–396. CRC Press, 1999. 8. L.Wiskott, J. M. Fellous, N. Kuiger, and C. von derMalsburg, “Face recognition by elastic bunch graph matching,” Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. 19, no. 7, pages 775–779, July 1997. 9. A.J.Goldstein, L.D. Harmon, and A.B Lesk, "Identification of Human Faces," Proc. IEEE, May 1971, Vol. 59, No. 5, 748- 760. 10. Biometrics,”Face Recognition”, National Science and Technical Council, 2006 http://www.biometrics.gov/Documents/FaceRec.pdf 11. Fischler, M. and Elschlager, R. (1973). ``The representation and matching of pictorial structures''. IEEE Transactions on Computers, C-22:67—92 12. M. Turk and A. Pentland. “Eigenfaces for recognition.” Journal of Cognitive Science, pp.71-86, 1991. 13. L. Wiskott, J. M. Fellous, N. Krüger and Christoph von der Malsburg, “Face Recognition by Elastic Graph Matching,” In Intelligent Biometric 110 Techniques in fingerprint and Face Recognition, CRC Press, Chapter 11, pp. 355-396, 1999. 14. Al-Amin Bhuiyan, and Chang Hong Liu, On Face Recognition using Gabor Filters proceedings of world academy of science, engineering and technology volume 22 july 2007 issn 1307-6884. 15. University of essex,uk faces94 face recognition data. |
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