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Face Recognition using Similarity Pattern of Image Directional Edge ResponseBASHAR, F. , KHAN, A. , AHMED, F. , KABIR, H.
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discrete cosine transform, face recognition, feature extraction, image texture analysis, pattern analysis
recognition(31), face(25), pattern(17), local(11), analysis(10), image(8), binary(6), vision(5), machine(5), information(5)
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About this article
Date of Publication: 2014-02-28
Volume 14, Issue 1, Year 2014, On page(s): 69 - 76
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2014.01011
Web of Science Accession Number: 000332062300011
SCOPUS ID: 84894635007
An effective face descriptor is critical for a successful face recognition system and must overcome the challenges of changing environment. The face representation must have discriminatory information and be computationally feasible for any face recognition system. In this paper we propose a new face descriptor, Similarity Pattern of Image Directional Edge Response (SPIDER), for face recognition. An image is divided into smaller local regions and 8 directional edge responses are generated for each pixel position in the regions. The regional cumulative response of each direction is calculated and a histogram is generated consisting of 8 bins, one for each of the directions. The SPIDER code is generated by calculating the similarity between the histogram of the local region around each pixel against the histogram of neighbor regions. The feature vector is projected to a low-dimension vector space using a dimension reduction method to minimize the classification time. Experiments using the proposed method were carried out on the FERET database and results show improved recognition rates indicating the robustness to changing environment, and a low classification time compared to the existing methods.
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| M. D. Kelly, "Visual Identification of people by computer", PhD Thesis, Stanford University, Stanford, CA, USA, 1971
 W. Zhao, R. Chellappa, P. J. Phillips and A. Rosenfeld, "Face Recognition: A Literature Survey", ACM Computing Surveys, vol. 35, no. 4, pp. 399-458, 2003.
[CrossRef] [Web of Science Times Cited 2572] [SCOPUS Times Cited 3738]
 D. S. Kim, I. J. Jeon, S. Y. Lee, P. K. Rhee and D. J. Chung, "Embedded face recognition based on fast genetic algorithm for intelligent digital photography," IEEE Transactions on Consumer Electronics, vol. 52, no. 3, pp.726-734, 2006.
[CrossRef] [Web of Science Times Cited 18] [SCOPUS Times Cited 26]
 F. Zuo and P. H. N. de With, "Real-time embedded face recognition for smart home", IEEE Transaction on Consumer Electronics, vol. 51, no. 1, pp. 183-190, 2005.
[CrossRef] [Web of Science Times Cited 52] [SCOPUS Times Cited 68]
 T. Jabid, M. H. Kabir, and O. Chae, "Local Directional Pattern (LDP) for face recognition", International Journal of Innovative Computing, Information and Conrol, vol. 8, no. 4, pp. 2423-2437, 2012
 M. A. Turk and A. P. Pentland, "Face recognition using eigenfaces," International Conference on Computer Vision and Pattern Recognition, IEEE, 1991, pp. 586-591.
 J. R. Movellan, M.S. Bartlett and T. J. Senjnowski, "Face recognition by independent component analysis," IEEE Transactions on Neural Networks, vol. 13, pp.1450-1465, 2002.
[CrossRef] [Web of Science Times Cited 913] [SCOPUS Times Cited 1289]
 C. Zhou, X. Wei, Q. Zhang and B. Xiao, "Image reconstruction for face recognition based on fast ICA", International Journal of Innovative Computing, Information and Control, vol. 4, no. 7, pp. 1723-1732, 2008.
 K. Etemad and R. Chellappa, "Discriminant Analysis for recognition of human face images," Journal of the optical Society of America, vol.14, pp. 1724-1733, 1997.
[CrossRef] [Web of Science Times Cited 442] [SCOPUS Times Cited 589]
 A. F. Frangi, J. Yang, D. Zhang and J. Y. Yang, "Two-dimensional PCA: a new approach to appearance-based face representation and recognition," IEEE Transaction on Pattern Analysis and Machine Intelligence, vol. 26, pp. 131-137, 2004.
[CrossRef] [Web of Science Times Cited 1533] [SCOPUS Times Cited 2233]
 I. G. P. Wijaya, K. Uchimura and Z. Hu, "Face recognition based on dominant frequency features and multi-resolution metric," International Journal of Innovative Computing, Information and Control, vol.5, no.3, pp. 641-651, 2009.
 Y. Zana and R. M. C. Jr., "Face recognition based on polar frequency features," ACM Transactions on Applied Perception, vol.3, no.1, pp. 62-82, 2006.
 B. Moghaddam, T. Jebara and A. Pentland, "Bayesian Face Recognition," Pattern Recognition, vol. 33, no. 11, pp. 1771-1782, 2000.
[CrossRef] [Web of Science Times Cited 320] [SCOPUS Times Cited 418]
 J. Zhou, Q. Ji and G. Nagy, "A comparative study of local matching approach for face recognition," IEEE Transactions on Image Processing, vol. 16, no. 10, pp. 2617-2628, 2007.
[CrossRef] [Web of Science Times Cited 164] [SCOPUS Times Cited 221]
 L. Wiskott, J. M.Fellous, N. Kuiger and C. von der Malsburg, "Face recognition using elastic bunch graph matching," IEEE Transaction on Pattern Analysis and Machine Intelligence, vol. 19, no. 7, pp. 775-779, 1997.
[CrossRef] [Web of Science Times Cited 1538] [SCOPUS Times Cited 2071]
 P. S. Penev and J. Atick, "Local feature analysis: A general statistical theory for object representation", Network: Computation in Neural Systems, vol. 7, no. 3, pp. 477-500, 1996.
[CrossRef] [Web of Science Times Cited 321]
 J. Kim, J. Choi and J. Yi, "Face recognition based on locally salient ICA information", Biometric Authentication Workshop, pp. 1-9, 2004.
 V. V. Starovoitov, D. I. Samal and D. V. Biriliuk, "Three approaches for face recognition," International Conference on Pattern Recognition and Image Analysis, 2002, pp. 707-7011.
 R. Jafri and H. R. Arabnia, "A survey of face recognition techniques," Journal of Information Processing Systems, vol. 5, no. 2, pp. 41-68, 2009.
 T. Ojala, M. Pietikainen and T. Maenpaa, "Multiresolution gray-scale and rotation invariant texture classification with local binary patterns," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, no. 7, pp.971-987, 2002.
[CrossRef] [Web of Science Times Cited 5147] [SCOPUS Times Cited 7008]
 T. Ahonen, A. Hadid and M. Pietikainen, "Face description with local binary patterns: Application to face recognition," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.28, no.12, pp.2037-2041, 2006.
[CrossRef] [Web of Science Times Cited 2046] [SCOPUS Times Cited 2805]
 R. Mattivi and L. Shao, "Human action recognition using LBP-TOP as sparse spatio-temporal feature descriptor", Proc. of International Conference of Computer Analysis of Image and Pattern, pp. 740-747,
 S. Zhao, Y. Gao and B. Zhang, "Sobel-LBP," IEEE International Conference on Image Processing, 2008, pp. 2144-2147.
 F. Ahmed, E. Hossain, A. S. M. H. Bari, M. S. Hossen, "Compound Local Binary Pattern (CLBP) for rotation invariant texture classification", International Journal of Computer Applications, vol. 33, no. 6, pp. 5-10, 2011.
 X. Tran and B. Triggs, "Enhanced local texture feature sets for face recognition under difficult lighting conditions," Analysis and Modeling of Faces and Gestures, pp. 168-182, 2007.
 O. Deniz, G. Bueno, J. Salido and F. de la Torre, "Face recognition using Histogram of Oriented Gradients," Pattern Recognition Letters, vol. 32, no. 12, pp. 1598-1603, 2011.
[CrossRef] [Web of Science Times Cited 125] [SCOPUS Times Cited 178]
 T. Jabid, M. H. Kabir and O. Chae, "Local Directional Pattern (LDP) for face recognition," International Conference on Consumer Electronics, pp. 329-330, 2010.
 J. Huang, P. J. Phillips, H. Wechsler and P. Rauss, "The FERET database and evaluation procedure for face recognition algorithms," Image and Vision Computing, vol.16, no.5, pp. 295-306, 1998.
[CrossRef] [Web of Science Times Cited 1087]
 Y. Mu, S. Yan, Y. Liu, S. T.Huang and B. Zhou, "Discriminative local binary patterns for human detection in personal album," IEEE Conference on Computer Vision and Pattern Recognition, 2008, pp. 1-8.
 Z. Sun, T. Tan and X. Qiu, "Graph matching iris image blocks with local binary pattern," Advances in Biometrics, 2005, pp. 366-372.
 X. Wang, H. Gong, H. Zhang, B .Li and Z. Zhuang, "Palm print Identification using Boosting Local Binary Pattern," International Conference on Pattern Recognition, 2006, pp. 503-506.
 R. C. Gonzalez, Digital Image Processing, Pearson, 2007
 Z. P. Rod, R. Adams, and H. Bolouri Dimensionality Reduction of Face Images Using Discrete Cosine Transforms for Recognition, IEEE Conference of Computer Vision and Pattern Recognition,
 J. Beveridge, D. Bolme, B. Draper, and M. Teixeira, "The CSU face identification evaluation system: Its purpose, features, and structure", Machine Vision and Applications, vol. 16, no. 2, pp. 128-138, 2005.
[CrossRef] [Web of Science Times Cited 57] [SCOPUS Times Cited 82]
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