Handwritten digit recognition using state-of-the-art techniques

Proceedings - International Workshop on Frontiers in Handwriting Recognition, IWFHR

Volumn , Issue , 2002, Pages 320-325

  Liu, Cheng Lin ^a   Nakashima, Kazuki ^a   Sako, Hiroshi ^a   Fujisawa, Hiromichi ^a  

^a HITACHI LTD   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

COMPARISON OF CLASSIFIERS; COMPLEMENTARY FEATURES; FEATURE EXTRACTION AND CLASSIFICATION; HANDWRITTEN DIGIT RECOGNITION; POLYNOMIAL CLASSIFIER; QUADRATIC DISCRIMINANTS; STATE-OF-THE-ART TECHNIQUES; SUPPORT VECTOR CLASSIFIERS;

DATABASE SYSTEMS; FEATURE EXTRACTION; STATISTICAL TESTS;

CLASSIFICATION (OF INFORMATION);

EID: 84893494973     PISSN: 15505235     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IWFHR.2002.1030930     Document Type: Conference Paper

References (22)

1. C.Y. Suen, J. Kim, K. Kim, Q. Xu, L. Lam, Handwriting recognition\-The last frontiers, Proc. 15th ICPR, Barcelona, 2000, Vol.4, pp.1-10.
2. D-S. Lee, S.N. Srihari, Handprinted digit recognition: A comparison of algorithms, Pr as. 3rd IWFHR, 1993, pp.153-164.
3. Y. LeCun, et al., Comparison of learning algorithms for handwritten digit recognition, Proc. Int. Conf. A-tificial Neural Networks, Prance, 1995, pp.53-60.
4. D. Wettschereck, T. Dietterich, Improving the performance of radial basis function networks by learning center locations, A dvanc es in Newt Information Processing Systems 4, Morgan-Kauffmann, 1992, pp.11331140.
5. U. Krefiel, J. Schiirmann, Pattern classification techniques based on function approximation, Handbook of Character R ecognition and Dimment Image Analysis, World Scientific, 1997, pp.49-78.
6. C-L. Liu, M. Nakaga w a, Evaluation of prototype learning algorithms for nearest neighbor classifier in application to handwritten character recognition, Pattern R ecognitiop,34(3): 601-615, 2001.
7. C-L. Liu, H. Sako, H. Fujisaw a,Learning quadratic discriminant function for handwritten character recognition, Proc. 16th ICPR Canada, 2002.
8. C. J. C. Surges, A tutorial on support vector machines for pattern recognition, Knowledge Discovery and Data Mining, 2(2): 1-43, 1998.
9. C-L. Liu, H. Sako, H. Fujisawa, Performance evaluation of pattern classifiers for handwritten character recognition, Int. J. Do cumentAnalysis and R ecgni-tion, 4(3): 191-204, 2002.
10. M. Yasuda, H. Fujisawa, An imprwement of correlation method for character recognition, T rans. IEIGE Japan J62-D(3): 217-224, 1979.
11. N. Hagita, S. Naito, I. Masuda, Handprinted Kanji characters recognition based on pattern matching method, Proc. ICTP 1983, pp.169-174.
12. C-L. Liu, Y-J. Liu, R-W. Dai, Preprocessing and statistical/structural feature extraction for handwritten numeral recognition, Progress of Handwriting R ecg-nition, World Scientific, 1997, pp. 161-168.
13. Y. LeCun, MNIST OCR data, http://www. re-searc h.att. com /yann /exdb/mnist /index.html.
14. C-L. Liu, M. Nakagaw a, Handwritten nmeral recognition using neural netw orks: improving the accuracy by discriminative training, Proc. 5th ICDAR, 1999, pp.257-260.
15. C-L. Liu, M. Koga, H. Sako, H. Fujisaw a Aspect ratio adaptive normalization for handwritten character recognition, A dvanes in Multimodal Interfaces-ICMI 2000, LNCS 1948, Springer, 2000, pp.418-425.
16. A. Ka w aura, et al., On-line recognition of freely handwritten Japanese characters using directional feature densities, Proc. 11th ICPR, 1992, Vol.11, pp.183186.
17. S-W. Lee, Multilayer cluster neural networkfor totally unconstrained handwritten numeral recognition, Neur al Netw orks 783-792, 1995.
18. T. Wakabayashi, S. Tsuruoka, F. Kimura, Y. Miyake, On the size and variable transformation of feature vector for handwritten character recognition, Trans. IE-ICE Japan, J76-D-II(12): 2495-2503, 1993.
19. B-H. Juang, S. Katagiri, Discriminative learning for minimization error classification, IEEE Trans. Signal Processing 40(12): 3043-3054, 1992.
20. F. Kimura, K. Takashina,S. Tsuruoka, Y. Miyake, Modified quadratic discriminant functions and the application to Chinese character recognition, IEEE Trans. Pattern A nalysis and Machine Intelligenc e 9(1): 149-153, 1987.
21. J.H. Friedman, Regularized discriminant analysis, J. A to. Statist. Ass, 84(405): 165-175, 1989.
22. O.L. Mangasarian, D.R. Musicant, Successiv eover-relaxation for support vector machines, IEEE Trans. Neur al Networks 10(5): 1032-1037, 1999.