Face Recognition System using Template Method

Face Recognition is a Biometric Application, which is used for Criminal Identification, Visitor Verification and many other Real Time Identification systems. We use basically two approaches for this system which are namely ‘Template Matching’ and ‘Feature Matching’. The Template Matching approach is independent of the features points, which we have used in this paper. Here we find the convolution values of the features for a test image and all the images in the database. In this work we introduce the novel idea of ‘Energies’. The distance algorithm states that the image in the database having the least distance with the test image in terms of Energies is the identified image.

[1]  Hong Yan,et al.  An Improved Method for Locating and Extracting the Eye in Human Face Images , 1996, Proceedings of 13th International Conference on Pattern Recognition.

[2]  Chin-Seng Chua,et al.  Facial feature detection and face recognition from 2D and 3D images , 2002, Pattern Recognit. Lett..

[3]  Mubarak Shah,et al.  A Fast algorithm for active contours and curvature estimation , 1992, CVGIP Image Underst..

[4]  Rama Chellappa,et al.  Human and machine recognition of faces: a survey , 1995, Proc. IEEE.

[5]  Ioannis Pitas,et al.  A novel method for automatic face segmentation, facial feature extraction and tracking , 1998, Signal Process. Image Commun..

[6]  Jian-Huang Lai,et al.  Face representation using independent component analysis , 2002, Pattern Recognit..

[7]  Demetri Terzopoulos,et al.  Snakes: Active contour models , 2004, International Journal of Computer Vision.

[8]  Ioannis Pitas,et al.  Digital Image Processing Algorithms , 1993 .

[9]  Josef Kittler,et al.  The Adaptive Hough Transform , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[10]  Thomas S. Huang,et al.  Human face detection in a complex background , 1994, Pattern Recognit..

[11]  Ioannis Pitas,et al.  Rule-based face detection in frontal views , 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[12]  Ioannis Pitas,et al.  Facial feature extraction and pose determination , 2000, Pattern Recognit..

[13]  Nicholas Ayache,et al.  Fast segmentation, tracking, and analysis of deformable objects , 1993, 1993 (4th) International Conference on Computer Vision.

[14]  Xiaobo Li,et al.  Face contour extraction from front-view images , 1995, Pattern Recognit..

[15]  Bülent Sankur,et al.  Facial feature extraction using genetic algorithms , 1996, 1996 8th European Signal Processing Conference (EUSIPCO 1996).

[16]  Steve R. Gunn,et al.  Snake head boundary extraction using global and local energy minimisation , 1996, Proceedings of 13th International Conference on Pattern Recognition.

[17]  Roberto Brunelli,et al.  Face Recognition: Features Versus Templates , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[18]  Linda G. Shapiro,et al.  Computer and Robot Vision , 1991 .