Dual classifier system for handprinted alphanumeric character recognition

Pattern Analysis and Applications

Volumn 1, Issue 3, 1998, Pages 155-162

  Chim, Y C ^a   Kassim, A A ^a   Ibrahim, Y ^a  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

Dual classifier systems; Handprinted character recognition; OCR; Radial basis functions

Indexed keywords

EID: 22444452953     PISSN: 14337541     EISSN: None     Source Type: Journal    
DOI: 10.1007/BF01259365     Document Type: Article

References (24)

1. Govindan VK, Shivaprasad AP. Character recognition - a review. Pattern Recognition 1990; 23: 671-683
2. Trier OD, Jain AK, Taxt T. Feature extraction methods for character recognition - a survey. Pattern Recognition 1996; 29(4): 641-662
3. Kundu A, Yang H, Bahl P. Recognition of handwritten word: first and second order hidden Markov model based approach. Pattern Recognition 1989; 22(3): 283-297
4. Bose CB, Kuo SS. Connected and degraded text recognition using hidden Markov model. Pattern Recognition 1994; 27(10): 1345-1363
5. Chen MY, Kundu A, Srihari SN. Variable duration hidden Markov model and morphological segmentation for handwritten word recognition. IEEE Transactions on Image Processing 1995; 4(12): 1675-1688
6. Vlontzos JA, Kung SY. Hidden Markov models for character recognition. IEEE Transactions on Image Processing 1992; 1(4): 539-543
7. Park HS, Lee SW. Off-line recognition of large-set handwritten characters with multiple hidden Markov models. Pattern Recognition 1996; 29(2): 231-244
8. Kim WS, Park RH. Off-line recognition of handwritten Korean and alphanumeric characters using hidden Markov models. Pattern Recognition 1996; 29(5): 845-858
9. Knerr S, Personnaz L, Dreyfus G. Handwritten digit recognition by neural networks with single-layer training. IEEE Transactions on Neural Networks 1992; 3(6): 962-968
10. Burges CJC et al. Off line recognition of handwritten postal words using neural networks. International Journal of Pattern Recognition and Artificial Intelligence 1993; 7(4): 689-704
11. Gupta A et al. An integrated architecture for recognition of totally unconstrained handwritten numerals. International Journal of Pattern Recognition and Artificial Intelligence 1993; 7(4): 757-773
12. Lee SW. Multilayer cluster neural network for totally unconstrained handwritten numeral recognition. Neural Networks 1995; 8(5): 783-792
13. Suen CY et al. Computer recognition of unconstrained handwritten numerals. Proceedings of the IEEE 1992; 80(7): 1162-1180
14. Xu L, Krzyzak A, Suen CY. Methods of combining multiple classifiers and their applications to handwriting recognition. IEEE Transactions on Systems, Man and Cybernetics 1992; 22(3): 418-435
15. Lam L, Suen CY. Optimal combinations of pattern classifiers. Pattern Recognition Letters 1995; 16(9): 945-954
16. Huang YS, Suen CY. A method of combining multiple experts for the recognition of unconstrained handwritten numerals. IEEE Transactions on Pattern Analysis and Machine Intelligence 1995; 17(1): 90-94
17. Musavi MT et al. On the training of radial basis function classifiers. Neural Networks 1992; 5: 595-603
18. Wettschereck D, Dietterich T. Improving the performance of radial basis function networks by learning center locations. Advances in Neural Information Processing Systems 1992; 4: 1133-1140
19. Albert A. Regression and the Moore-Penrose Pseudoinverse. Academic Press, 1972
20. Cheng HD, Xia DC. A novel parallel approach to character recognition and its VLSI implementation. Pattern Recognition 1996; 29(1): 97-119
21. Duda RO, Hart PE. Pattern Classification and Scene Analysis. Wiley, 1973
22. Prewitt JMS. Object enhancement and extraction. In Picture Processing and Psychopictorics, Lipkin B, Rosenfeld A. (eds). Academic Press, 1970; 75-149
23. Kirsh R. Computer determination of the constituent structure of biological images. Computers in Biomedical Research 1971; 4: 315-328
24. Chen YS, Hsu WH. A modified fast parallel algorithm for thinning digital patterns. Pattern Recognition Letters 1988; 7: 99-106