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Enhancing Face Recognition using Average per Region
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 65 - Number 3 |
| Year of Publication: 2013 |
| Authors: Basheer M. Nasef, Ibrahim E. Ziedan |
10.5120/10905-5832
|
Basheer M. Nasef, Ibrahim E. Ziedan . Enhancing Face Recognition using Average per Region. International Journal of Computer Applications. 65, 3 ( March 2013), 19-23. DOI=10.5120/10905-5832
Abstract
Face recognition is concerned with the problem of correctly identifying face images and assigning them to persons in a database. This finds many practical applications in, e. g. , surveillance, identification systems and access control. In this paper, a face recognition method, with moderate computational requirements while preserving an acceptable recognition rate, is proposed based on the "average" features of gray images. The advantage of using average matching is that the structure of the face is strongly represented in its description along with its algorithmic and computational simplicity that makes it suitable for hardware implementation. The proposed technique is tested on the ORL face database benchmark and compared to well-established face recognition algorithms, namely Histogram, Hybrid Histogram & Eigen value (HHE). The results show the superiority of the new method over these methods in terms of recognition accuracy and computational time.
References
- Zhao W, Chellappa R, Rosenfeld A, Phillips PJ (2000) Face recognition: a literature survey. CS-Tech Report-4167, University of Maryland
- Andrea F, Michele N, Daniel R, Gabriele S, 2007. 2D and 3D face recognition: A survey. PatRec Lett. 28, 1885–1906.
- Jie Yang, Xufeng Ling, Yitan Zhu, Zhonglong Zheng, 2008. A face detection and recognition system in color image series. Mathematics and Comp. in Simulation 77 (2008) 531–539
- Rein-Lien Hsu, "Face Detection and Modeling for Recognition," PhD thesis, Department of Comp. Science & Eng. , Michigan State University, USA, 2002.
- S. T. Gandhe, K. T. Talele, and A. G. Keskar, "Face Recognition Using Contour Matching", IAENG(2008) , IJCS_35_2_06
- S. T. Gandhe, K. T. Talele, A. G. Keskar, "Face Recognition Using Isodensity Maps-A Neural Network Approach", in Ist International Conference on Emerging Applications of Information Technology (EAIT) organized by Computer Society Of India, Kolkata Chapter, Kolkata, pp. 129-132,11,12th February 2006.
- Tolba, El-Baz, El-Harby, "Face Recognition – A Literature Review", (IJSP) International Journal of Signal Processing, Vol. 2, No. 2, 2005, pp. 88-103
- Ming – Hsuan Yang, David J. Kriegman, Narendra Ahuja, "Detecting Faces In Images", IEEE Trans. on Pattern Analysis and Machine Intell. , Vol. 24, No. 1, 2002.
- ORL, 1992. The ORL face database at the AT&T (Olivetti) Research Laboratory. Available from http://www. uk. research. att. com/ facedatabase. html
- W. Zhao, R. Chellappa, A. Rosenfeld, and P. Phillips. Face recognition: A literature survey, 2000.
- Shang-Hung Lin, Ph. D. "An introduction to face recognition technology". Informing Science Special Issue on Multimedia Informing Technologies-Part2 V3 No 1, 2000.
- Cevikalp, H. , Neamtu, M. , Wilkes, M. , Barkana, A. , 2005. Discriminative common vectors for face recognition. IEEE Trans. Pattern Anal. Machine Intell. 27 (1), 4–13.
- He. Gulati, De. Aggarwal, Amit Verma, Prvinder S. Sandhu, Face Recognition using Hybrid Histogram & Eigen value Approach, International Journal of Research in Engineering and Technology (IJRET) Vol. 1 No. 1 (2012).
- Sarbjeet Singh, Meenakshi Sharma, N. Suresh Rao, Robust & Accurate Face Recognition using Histograms, International Journal of Management, IT and Engineering (IJMIA) Vol. 2 No. 4 (2012), ISSN 2249- 0558.
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