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Face Recognition Robust to Brightness, Contrast, Scale, Rotation and Translation  

이형지 (인하대학교 전자공학과)
정재호 (인하대학교 전자공학과)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.40, no.6, 2003 , pp. 149-156 More about this Journal
Abstract
This paper proposes a face recognition method based on modified Otsu binarization, Hu moment and linear discriminant analysis (LDA). Proposed method is robust to brightness, contrast, scale, rotation, and translation changes. Modified Otsu binarization can make binary images that have the invariant characteristic in brightness and contrast changes. From edge and multi-level binary images obtained by the threshold method, we compute the 17 dimensional Hu moment and then extract feature vector using LDA algorithm. Especially, our face recognition system is robust to scale, rotation, and translation changes because of using Hu moment. Experimental results showed that our method had almost a superior performance compared with the conventional well-known principal component analysis (PCA) and the method combined PCA and LDA in the perspective of brightness, contrast, scale, rotation, and translation changes with Olivetti Research Laboratory (ORL) database and the AR database.
Keywords
LDA; PCA;
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Times Cited By KSCI : 3  (Citation Analysis)
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1 R. Chellappa and S. Sirohey, 'Human and Machine Recognition of Faces: A Survey,' Proceedings of the IEEE. vol. 83, no. 5. May 1995   DOI   ScienceOn
2 S. Pankanti, R. M. Bolle, and A. Jain, 'Biometrics: The Future of Identification', Computer Magazine, pp. 46-49, Feb. 2000   DOI   ScienceOn
3 X. Y. Zeng, Y. W. Chen, and Z. Nakao, 'Image Feature Representation by the Subspace of Nonlinear PCA,' in Proc. International Conference on Pattern Recognition, pp. 11-15, Aug. 2002   DOI
4 K. I. Kim, K Jung, and H. J. Kim, 'Face Recognition Using Kernel Principal Component Analysis,' IEEE Signal Processing Letters, vol. 9, no. 2, Feb. 2002   DOI   ScienceOn
5 B. Due, S. Fisher, and J. Bigun, 'Face Authentication with Gabor Information on Deformable Graphs,' IEEE Trans. on Image Processing, vol. 8, no. 4, April 1999   DOI   ScienceOn
6 S. C. Lee, H. S. Kim, S. J. Park, and S. H. Park, 'Face Recognition Technology in the Dynamic Link Architecture,' in Proc. the International Conference on Electrical Engineering, pp. 265-268, 1999
7 L. Wiskott, J. M. Fellous, N. Kruger, and C. Malsburg, 'Face Recognition by Elastic Bunch Graph Matching,' IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 19, no. 7, pp. 775-779, 1997   DOI   ScienceOn
8 Y. Cao and K. H. Leung, 'Face Recognition Using Line Edge Map,' IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 24, no. 6, pp. 764-779, 2002   DOI   ScienceOn
9 심영미, 장주석, 김종규, 'Fourier 변환된 얼굴의 진폭스펙트럼의 Karhunen-Loeve 근사 방법에 기초한 변위불변적 얼굴인식,' 전자공학회논문지, 제 35권, C편, 제 3호, 1998   과학기술학회마을
10 M. Nixon, 'Automated facial recognition and its potential for security,' in IEE Colloq, Dig. (80): Colloq. on MMI in Computer Security, pp. 5/1-4, 1986
11 A. P. Pentland and M. A. Turk, 'Face Recognition Using Eigenfaces,' in Proc. the International Conference on Pattern Recognition, pp. 586-591, 1994
12 P. N. Belhumeur, J. P. Hespanha, and D. J. Kriegman, 'Eigenfaces vs. Fisherfaces : recognition using class specific linear projection,' IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 19, no. 7, pp. 711-720, July 1997   DOI   ScienceOn
13 N. Otsu, 'A threshold selection method from gray level histogram,' IEEE SMC-9, no. 1, pp. 62-66, 1979
14 M. S. Oh, D. W. Kim, and D. S. Jeong, 'Face Identification System Using Combined Facial Features and Counter-Propagation Neural Network,' 신호처리합동학술대회, 제 6권, pp. 266-269, 1993
15 A. M. Martinez and R. Benavente, 'The AR Face Database,' CVC Technical Report no. 24, June 1998
16 김광섭, 이상묵, 정동석, '윤곽선 방향의 히스토그램과 Sampled Spot Matching을 이용한 이치형상의 인식 알고리즘,' 전자공학회논문지, vol. 28, no. 10, pp. 69-77, 1992   과학기술학회마을
17 K. Fukunaga, Introduction to Statistical Pattern Recogntion, New York Academic, 1972
18 H. J. Lee and J. H. Chung, 'Brightness, Contrast, Scaling, Rotation and Translation Invariant Feature Extraction by Multi-level Thresholding and Moment,' Submitted IEICE
19 D. L. Swets, and J. Weng, 'Using discriminant eigenfeatures for image retrieval,' IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 18, no. 8, pp. 831-836, August 1995   DOI   ScienceOn
20 S. Z. Li and J. Lu, 'Face recognition using the nearest feature line method,' IEEE Trans. Neural Networks, vol. 10, pp. 439-443, Mar. 1999   DOI   ScienceOn
21 R. C. Gonzalez, P. Wintz, Digital image processing, Addision-Wesley, 1987
22 M. K. Hu, 'Pattern recognition by moment invariants,' Proc. IEEE, vol. 49, no. 9, p. 1428, Sept. 1961
23 이형지, 정재호, 'Fisherface 알고리즘과 Fixed Graph Matching을 이용한 얼굴 인식,' 전자공학회논문지, 제 38권, SP편, 제 6호, 2001   과학기술학회마을
24 M. K. Hu, 'Visual pattern recognition by moment invariants,' IRE Transactions on Information Theory, vol. 17-8, no. 2, pp. 179-187, Feb. 1962   DOI
25 J. Lu, K. N. Plataniotis, and A. N. Venetsanopoulos, 'Face Recognition Using LDA-Based Algorithms,' IEEE Trans. Neural Networks, vol. 14, no. 1, pp. 195-200, Jan. 2003   DOI   ScienceOn