High accuracy handwritten Chinese character recognition using LDA-based compound distances

Pattern Recognition

Volumn 41, Issue 11, 2008, Pages 3442-3451

  Gao, Tian Fu ^a   Liu, Cheng Lin ^a  

^a INSTITUTE OF AUTOMATION   (China)

Author keywords

Compound distance; Compound Mahalanobis function; Handwritten Chinese character recognition; LDA

Indexed keywords

CHARACTER RECOGNITION; CLASSIFICATION (OF INFORMATION); CLASSIFIERS; DISCRIMINANT ANALYSIS; ELECTRIC FILTERS; ERROR ANALYSIS; ESTIMATION; LEARNING SYSTEMS; OBJECT RECOGNITION; QUADRATIC PROGRAMMING;

(2+1)-DIMENSIONAL; (SPM) CLASSES; DISCRIMINABILITY; DISCRIMINANT VECTORS; ELSEVIER (CO); ERROR RATE (ER); FEATURE SPACES; HANDWRITTEN CHINESE CHARACTER RECOGNITION; HIGH ACCURACY; HIGH-DIMENSIONAL; LINEAR DISCRIMINANT ANALYSIS (CLDA); MAHALANOBIS; MODIFIED QUADRATIC DISCRIMINANT FUNCTION (MQDF); ONE-DIMENSIONAL;

VECTORS;

EID: 48149088783     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2008.04.011     Document Type: Article

References (23)

1. Dai R., Liu C., and Xiao B. Chinese character recognition: history, status and prospects. Frontiers Comput. Sci. China 1 2 (2007) 126-136
2. Kimura F., Takashina K., Tsuruoka S., and Miyake Y. Modified quadratic discriminant functions and its application to Chinese character recognition. IEEE Trans. Pattern Anal. Mach. Intell. 9 1 (1987) 149-153
3. Kimura F., Wakabayashi T., Tsuruoka S., and Miyake Y. Improvement of handwritten Japanese character recognition using weighted direction code histogram. Pattern Recognition 30 8 (1997) 1329-1337
4. Kato N., Suzuki M., Omachi S., Aso H., and Nemoto Y. A handwritten character recognition system using directional element feature and asymmetric Mahalanobis distance. IEEE Trans. Pattern Anal. Mach. Intell. 21 3 (1999) 258-262
5. T. Kawatani, Handwritten Kanji recognition with determinant normalized quadratic discriminant function, in: Proceedings of the 15th ICPR, vol. 2, Barcelona, Spain, 2000, pp. 343-346.
6. C.-L. Liu, High accuracy handwritten Chinese character recognition using quadratic classifiers with discriminative feature extraction, in: Proceedings of the 18th ICPR, vol. 2, Hong Kong, 2006, pp. 942-946.
7. Liu C.-L., Sako H., and Fujisawa H. Discriminative learning quadratic discriminant function for handwriting recognition. IEEE Trans. Neural Networks 15 2 (2004) 430-444
8. Biem A., Katagiri S., and Juang B.-H. Pattern recognition using discriminative feature extraction. IEEE Trans. Signal Process. 45 2 (1997) 500-504
9. Fu H.C., and Xu Y.Y. Multilinguistic handwritten character recognition by Bayesian decision-based neural networks. IEEE Trans. Signal Process. 46 10 (1998) 2781-2789
10. Dong J.X., Krzyzak A., and Suen C.Y. An improved handwritten Chinese character recognition system using support vector machine. Pattern Recognition Lett. 26 12 (2005) 1849-1856
11. Saruta K., Kato N., Abe M., and Nemoto Y. High accuracy recognition of ETL9B using exclusive learning neural network-II (ELNET-II). IEICE Trans. Inf. Syst. 79-D 5 (1996) 516-521
12. T. Kawatani, H. Shimizu, Handwritten Kanji recognition with the LDA method, in: Proceedings of the 14th ICPR, vol.2, Brisbane, Australia, 1998, pp. 1031-1035.
13. Ishii T., Waizumi Y., Kato N., and Nemoto Y. Recognition system for handwritten characters by alternative method using neural network. Trans. IEICE Jpn. J83-D-II 3 (2000) 988-995
14. Y. Jin, S. Ma, Pairwise classifier combination and its application on Chinese character recognition, in: Proceedings of the 5th World Congress on Intelligent Control and Automation, vol. 5, Hangzhou, China, 2004, pp. 4075-4078.
15. Jin Y., and Ma S. Experiment on linear classification of Chinese character. J. Chinese Inf. Process. 14 2 (2002) 55-60
16. Suzuki M., Ohmachi S., Kato N., Aso H., and Nemoto Y. A discrimination method of similar characters using compound Mahalanobis function. Trans. IEICE Jpn J80-D-II 10 (1997) 2752-2760
17. Nakajima T., Wakabayashi T., Kimura F., and Miyake Y. Accuracy improvement by compound discriminant functions for resembling character recognition. Trans. IEICE Jpn. J83-D-II 2 (2000) 623-633
18. H. Liu, X. Ding. Handwritten character recognition using gradient feature and quadratic classifier with multiple discrimination schemes, in: Proceedings of the 8th ICDAR, Seoul, Korea, 2005, pp. 19-23.
19. Fukunaga K. Introduction to Statistical Pattern Recognition. second ed. (1990), Academic Press, New York
20. T.-F. Gao, C.-L. Liu, LDA-based compound distance for handwritten Chinese character recognition, in: Proceedings of the 9th ICDAR, Curitiba, Brazil, 2007, pp. 904-909.
21. Loog M., Duin R.P.W., and Haeb-Umbach R. Multiclass linear dimension reduction by weighted pairwise Fisher criterion. IEEE Trans. Pattern Anal. Mach. Intell. 23 7 (2001) 762-766
22. C.-L. Liu, H. Sako, H. Fujisawa, Handwritten Chinese character recognition: alternatives to nonlinear normalization, in: Proceedings of the 7th ICDAR, Edinburgh, Scotland, 2003, pp. 524-528.
23. Liu C.-L., Nakashima K., Sako H., and Fujisawa H. Handwritten digit recognition: investigation of normalization and feature extraction techniques. Pattern Recognition 37 2 (2004) 265-279