Feature Extraction Based on Symmetrical ICA and Its Application to Face Recognition
ZHENG YuJie1, YANG JingYu1, WU XiaoJun2,3, YU DongJun1
1.Department of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing 210094 2.School of Electronics and Information, Jiangsu University of Science and Technology, Zhenjiang 212003 3.Robotics Laboratory, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110015
Abstract Independent Component Analysis (ICA) has been extensively used in the field of signal processing and image processing. In this paper, a new algorithm called symmetrical ICA (SICA) based on facial symmetry is proposed. This algorithm is based on the theory of function decomposition in algebra and mirror symmetry in geometry. In this algorithm, mirror transform is firstly introduced. Then, even/odd symmetrical samples are produced based on the theory of the even/odd decomposition principle, and the even/odd independent components are extracted from the corresponding samples respectively. Both theoretical analysis and experimental results demonstrate that this algorithm not only enlarges the number of training samples, but also remarkably raises the recognition rate. Experiment results also show this algorithm is not sensitive to the illumination variation of human faces.
ZHENG YuJie,YANG JingYu,WU XiaoJun等. Feature Extraction Based on Symmetrical ICA and Its Application to Face Recognition[J]. , 2006, 19(1): 116-121.
[1] Swets D L, Weng J. Using Discriminant Eigenfeatures for Image Retrieval. IEEE Trans on Pattern Analysis and Machine Intelligence, 1996, 18(8): 831-836 [2] Belhumeur V, Hespanha J, Kriegman D. Eigenfaces vs Fisherfaces: Recognition Using Class Specific Linear Projection. IEEE Trans on Pattern Analysis and Machine Intelligence, 1997, 19 (7): 711-720 [3]Yang J, Yang J Y. Why Can LDA Be Performed in PCA Transformed Space? Pattern Recognition, 2003, 36(2): 563-566 [4]Hong Z Q, Yang J Y. Algebraic Feature Extraction of Images for Recognition. Acta Automatica Sinica, 1992, 18(2): 233-238 (in Chinese) (洪子泉, 杨静宇. 用于图像识别的图像代数特征抽取, 自动化学报, 1992, 18(2): 233-238) [5]Liu C J, Wechsler H. Robust Coding Schemes for Indexing and Retrieval from Large Face Databases. IEEE Trans on Image Processing, 2000, 9(1): 132-137 [6]Etemad K, Chellappa R. Face Recognition Using Discriminant Eigenvectors. In: Proc of IEEE International Conference on Acoustics, Speech, and Signal Processing. Atlanta, USA, 1996, Ⅳ: 2148-2151 [7]Comon P. Independent Component Analysis-A New Concept? Signal Processing, 1994, 36(3): 287-314 [8]Yang Z Q, Li Y, Hu D W. Independent Component Analysis: A Survey. Acta Automatica Sinica, 2002, 28(5): 762-772 (in Chinese) (杨竹青,李 勇,胡德文.独立成分分析方法综述.自动化学报, 2002, 28(5): 762－772) [9]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 [10]Liu C J, Wechsler H. Comparative Assessment of Independents Component Analysis (ICA) for Face Recognition. In: Proc of the 2nd International Conference on Audio-and Video-Based Biometric Person Authentication. Washington, USA, 1999, 22-24 [11]Hyvrinen A. Survey on Independent Component Analysis. Neural Computing Surveys, 1999, 2(4): 94-128 [12]Hyvrinen A. Fast and Robust Fixed-Point Algorithms for Independent Component Analysis. IEEE Trans on Neural Networks, 1999, 10(3): 626-634 [13]Hyvrinen A, Oja E. A Fast Fixed-Point Algorithm for Independent Component Analysis. Neural Computations, 1997, 9(7): 1483-1492 [14]Karhunen J, Oja E, Wang L, Vigrio R, Jontsensalo J. A Class of Neural Networks for Independent Component Analysis. IEEE Trans on Neural Networks, 1997, 8(3): 486-504 [15]Kirby M, Sirovich L. Application of the Karhunen-Loeve Procedure for the Characterization of Human Faces. IEEE Trans on Pattern Analysis and Machine Intelligence, 1990, 12(1): 103-108 [16]Marcel S. A Symmetric Transformation for LDA-Based Face Verification. In: Proc of the 6th International Conference on Automatic Face and Gesture Recognition. Seoul, Korea, 2004, 207-212 [17]Phillips P J, Wechsler H, Huang J, Rauss P. The FERET Database and Evaluation Procedure for Face Recognition Algorithms. Image and Vision Computing Journal, 1998, 16(5): 295-306 [18]Déniz O, et al. Face Recognition Using Independent Component Analysis and Support Vector Machines. Pattern Recognition Letters, 2003, 24(13): 2153-2157
2006, Vol. 19 
