|
|
Face Recognition Based on Enhanced Gabor Feature and Direct Fractional-Step Linear Discriminant Analysis |
ZOU Jian-Fa1, WANG Guo-Yin1, GONG Xun2 |
1.Institute of Computer Science and Technology,Chongqing University of Posts and Telecommunications,Chongqing 400065 2.School of Information Science and Technology,Southwest Jiaotong University,Chengdu 610031 |
|
|
Abstract Gabor features can effectively represent the local features of face image with different directions and scales. However, traditional Gabor features based algorithms neglect the global features of the original image. Enhanced Gabor features (EGF) is developed in this paper by combining Gabor features and information extracted from the original image. A face recognition method is further proposed based on EGF and direct fractional-step linear discriminant analysis algorithm (DF_LDA). Experiment results of simulation on Yale, ORL and Georgia face databases show that EGF can effectively improve the face recognition rate compared with the traditional Gabor features.
|
Received: 12 May 2009
|
|
|
|
|
[1] Turk M, Pentland A. Eigenfaces for Recognition. Journal of Cognitive Neuroscience, 1991, 3(1): 71-86 [2] Belhumeur P N, Hespanda J, Kriegeman D. Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection. IEEE Trans on Pattern Analysis and Machine Intelligence, 1997, 19(7): 711-720 [3] Bartlett M S, Movellan J R, Sejnowski T J. Face Recognition by Independent Component Analysis. IEEE Trans on Neural Networks, 2002, 13(6): 1450-1464 [4] Lu J, Plataniotis K N, Venetsanopoulos A N. Face Recognition Using LDA-Based Algorithms. IEEE Trans on Neural Networks, 2003, 14(1): 195-200 [5] Porat M, Zeevi Y. The Generalized Gabor Scheme of Image Representation in Biological and Machine Vision. IEEE Trans on Pattern Analysis and Machine Intelligence, 1988, 10(4): 452-468 [6] Wiskott L, Fellous J M, Kruger N, et al. Face Recognition by Elastic Bunch Graph Matching. IEEE Trans on Pattern Analysis and Machine Intelligence, 1997, 19(7): 775-779 [7] Liu Chengjun, Wechsler H. Gabor Feature Based Classification Using the Enhanced Fisher Linear Discriminant Model for Face Recognition. IEEE Trans on Image Processing, 2002, 11(4): 467-476 [8] Zhang Wenzhao, Shan Shiguang, Zhang Hongming,et al. Histogram Sequence of Local Gabor Binary Pattern for Face Description and Identification. Journal of Software, 2006, 17(12): 2508-2517 (in Chinese) (张文超,山世光,张洪明,等.基于局部Gabor 变化直方图序列的人脸描述与识别方法.软件学报, 2006, 17(12): 2508-2517) [9] Shen Linlin, Bai Li. Mutual Boost Learning for Selecting Gabor Features for Face Recognition. Pattern Recognition Letters, 2006, 27(15):1758-1767 [10] Long Fei, Dong Huailin, Wang Beizhan, et al. Gabor Representation Based Probabilistic Subspace Analysis for Face Recognition. Journal of Electronics Information Technology, 2007, 29(3): 626-630 (in Chinese) (龙 飞,董槐林,王备战,等.一种基于Gabor描述的概率子空间人脸识别方法.电子与信息学报, 2007, 29(3): 626-630) [11] Yu Hua, Yang Jie. Direct LDA Algorithm for High Dimensional Data with Application to Face Recognition. Pattern Recognition, 2001, 34(10): 2067-2070 [12] Lotlikar R, Kothari R. Fractional-Step Dimensionality Reduction. IEEE Trans on Pattern Analysis and Machine Intelligence, 2000, 22(6): 623-627 [13] Lu Juwei, Plataniotis K N, Venetsanopoulos A N. Regularization Studies of Linear Discriminant Analysis in Small Sample Size Scenarios with Application to Face Recognition. Pattern Recognition Letters, 2005, 26(2): 181-191 [14] Bian Zhaoqi, Zhang Xuegong. Pattern Recognition. 2nd Edition. Beijing, China: Tsinghua University Press, 2000 (in Chinese) (边肇祺,张学工. 模式识别.第2版.北京:清华大学出版社, 2000) [15] Yale University Center for Computational Vision and Control. The Yale Face Database[DB/OL]. [2009-02-26]. http://cvc.yale.edu/projects/yalefaces/yalefaces.html [16] ATT Laboratories Cambridge. The ORL Database of Faces[DB/OL]. [2009-02-26]. http://www.cl.cam.ac.uk/research/dtg/attarchive/facedatabase.html [17] Georgia Institute of Technology. The Georgia Tech Face Database[DB/OL]. [2009-02-26]. http://www.anefian.com/face_reco.htm |
|
|
|