A Novel Hybrid Feature Extraction Technique For Face Recognition

P Naveen Kumar, B Naresh Kumar, G.srinivasa Rao

Abstract


Face recognition is a computer for identifying and retrieving desired images from a large collection on the basis of features(color, texture, shape..).CBIR system is generally used in security, medicine, entertainment…etc. Interesting method for dimensionality reduction is subspace analysis. Images are portioned into sub images by using sub band decomposition or orthogonal transform to detect local features. Shape feature of an image can be represented using various moments. Image representation using moments has desirable properties of rotation invariance, robust to noise, expression efficiency, effective ness, and multi level representation for describing various shapes of patterns. Further in this work different distance measure like Minkowski distance, Manhatten distance, Euclidean distance etc. will be used to test the performance of the proposed methods


Keywords


PCA, LDA,ICA and distance techniques

References


] A.S.Georghiades, P. N. Belhumeur, and D. J. Kriegman, “From few to many: Illumination cone models for face recognition under variable lighting and pose,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 23, no. 6, pp. 643–660, Jun. 2001.

] R.Basri and D. Jacobs, Lambertian Reflectance and Linear Subspaces, NEC Research Inst. Tech. Rep. 2000-172R, 2000, Tech. Rep.

] R.Basri and D.W. Jacobs,“Lambertian reflectance and linear sub¬spaces,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 25, no. 2, pp. 218–233, Feb. 2003.

] Bhabatosh Chanda and Dwijest Dutta Majumder, 2002, Digital Image Processing and Analysis.

] R.W.Jr. Weeks,(1996). Fundamental of Electronic ImageProcessing Bellingham SPIE Press

] A.K.Jain, Fundamentals of Digital Image Processing.Englewood Cliffs, NJ: Prentice Hall, 1989.

] R.M. Haralick, and L.G. Shapiro, Computer and RobotVision, Vol-1, Addison Wesley, Reading, MA, 1992.

] R. Jain, R. Kasturi and B.G. Schunck, Machine Vision, McGraw-Hill International Edition, 1995.

] W. K. Pratt, Digital image processing, Prentice Hall, 1989.

] A.C. Bovik, Digital Image Processing Course Notes, Dept. ofElectrical Engineering, U. of Texas at Austin, 1995.

] D. W. Jacobs, P. N. Belhumeur, and R. Basri, “Comparing images under variable illumination,” in Proc. IEEE Conf. Computer Vision and Pattern Recognition, 1998, pp. 610–617.

] J. Tumblin and G. Turk, “LCIS: A boundary hierarchy for detail-pre¬serving contrast reduction, in ACM SIGGraph, 1999, pp. 83–90.

] A. S. Georghiades, P. N. Belhumeur, and D. J. Kriegman, “From few to many: Generative models for recognition under variable pose and illumination,” in Proc. 4th IEEE Int. Conf. Automatic Face and Gesture Recognition, 2000, pp. 277–284.


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