Structural primitive extraction and coding for handwritten numeral recognition

Pattern Recognition

Volumn 31, Issue 5, 1998, Pages 493-509

  Hu, Jianming ^a   Yan, Hong ^b  

^a XIDIAN UNIVERSITY   (China)

^b General Network Corporation   (United States)

Author keywords

Handwritten numeral recognition; Skeleton coding; Skeleton decomposition; Structural approach

Indexed keywords

ALGORITHMS; CODES (SYMBOLS); DATABASE SYSTEMS; FEATURE EXTRACTION; IMAGE CODING; IMAGE QUALITY; PATTERN MATCHING; PATTERN RECOGNITION;

HANDWRITTEN NUMERAL RECOGNITION; SKELETON CODING; SKELETON DECOMPOSITION; STRUCTURAL PRIMITIVE EXTRACTION;

CHARACTER RECOGNITION;

EID: 0032064080     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0031-3203(97)00095-2     Document Type: Article

References (26)

1. P. Siy and C. S. Chen, Fuzzy logic for handwritten numeral character recognition, IEEE Trans. System Man Cybernet. 4, 570-575 (1974).
2. F. Ali and T. Pavlidis, Syntactic recognition of handwritten numerals, IEEE Trans. System Man Cybernet. 1, 537-541 (1977).
3. B. Duerr, W. Haettich, H. Tropf and G. Winkler, A combination of statistical and syntactical pattern recognition applied to classification of unconstrained handwritten numerals, Pattern Recognition 21, 189-199 (1980).
4. G. Baptista and K. M. Kulkarni, A high accuracy algorithm for recognition of handwritten numerals, Pattern Recognition 21, 287-291 (1988).
5. L. Lam and C. Y. Suen, Structural classification and relaxation matching of totally unconstrained handwritten ZIP-code numbers, Pattern Recognition 21, 19-31 (1988).
6. C. Y. Suen, C. Nadal, R. Legault, T. A. Mai and L. Lam, Computer recognition of unconstrained handwritten numerals, Proc. IEEE 80, 1162-1180 (1992).
7. S. Mori, C. Y. Suen and K. Yamamoto, Historical review of OCR research and development, Proc. IEEE 80, 1029-1058 (1992).
8. H. Nishida and S. Mori, An algebraic approach to automatic construction of structural models, IEEE Trans. Pattern Anal. Mach. Intett. 15(12), 1298-1311 (1993).
9. A. Marcelli, N. Likhareva and T. Pavlidis, A structural indexing method for character recognition, Proc. 2nd Int. Conf. Document Analysis and Recognition, Tsukuba Science City, Japan, pp. 175-178 (1993).
10. A. Amin and W. H. Wilson, Hand-printed character recognition system using artificial neural networks, Proc. 2nd Int. Conf. on Document Analysis and Recognition, Tsukuba Science City, Japan, pp. 943-946 (1993).
11. G.-E. Wang and J.-F. Wang, A multi-layer classifier for recognition of unconstrained handwritten numerals, Proc. 3rd Int. Conf. Document Analysis and Recognition, Montréal, Canada, Vol. II, pp. 849-852 (1995).
12. G. Congedo, G. Dimauro, S. Impedovo and G. Pirlo, A structural method with local refining for handwritten character recognition, Proc. 3rd Int. Conf. Document Analysis and Recognition, Montréal, Canada, Vol. II, pp. 853-856 (1995).
13. L. Heutte, J. V. Moreau, T. Paquet, Y. Lecourtier and C. Olivier, Combining structural and statistical features for the recognition of handwritten characters, Proc. 13th Int. Conf. Pattern Recognition, Vienna, Austria, Vol. II, Track B, pp. 210-214 (1996).
14. J. Hu and H. Yan, Structural decomposition and description of printed and handwritten characters, Proc. 13th Int. Conf. Pattern Recognition, Vienna, Austria, Vol. III, Track C, pp. 230-234 (1996).
15. M. Shridhar and A. Badreldin, High accuracy character recognition algorithm using Fourier and topological descriptors, Pattern Recognition 17, 515-524 (1984).
16. T. Taxt, J. B. Olafsdottir and M. Daehlen, Recognition of handwritten symbols, Pattern Recognition 23, 1155-1166 (1990).
17. P. Gader, B. Forester, M. Ganzberger, A. Gillies, B. Mitchell, M. Whalen and T. Yocum, Recognition of handwritten digits using template and model matching, Pattern Recognition 24, 421-431 (1991).
18. H. Yan, Handwritten digit recognition using an optimized nearest neighbor classifier, Pattern Recognition Lett. 15, 207-211 (1994).
19. Z. Chi, J. Wu and H. Yan, Handwritten numeral recognition using self-organizing maps and fuzzy rules, Pattern Recognition 28, 59-66 (1995).
20. J. Cao, M. Ahmadi and M. Shridhar, Recognition of handwritten numerals with multiple feature and multistage classifier, Pattern Recognition 28, 153-160 (1995).
21. N. W. Strathy and C. Y. Suen, A new system for reading handwritten zip codes, Proc. 3rd Int. Conf. Document Analysis and Recognition, Montréal, Canada, Vol. I, pp. 74-77 (1995).
22. J. Mao, K. Mohiuddin, and T. Fujisaki, A two-stage multi-network OCR system with a soft pre-classifier and a network selector, Proc. 3rd Int. Conf. Document Analysis and Recognition, Montreal, Canada, Vol. I, pp. 78-81, (1995).
23. S.-W. Lee, Off-line recognition of totally unconstrained handwritten numerals using multilayer cluster neural network, IEEE Trans. Pattern Anal. Mach. Intell. 18(6), 648-652 (1996).
24. T. Y. Zhang and C. Y. Suen, A fast parallel algorithm for thinning digital patterns, Comm. ACM 27, 236-239 (1984).
25. R. C. Gonzalez and R. E. Woods, Digital Image Processing, Addison-Wesley, New York (1992).
26. M. Garris and R. Wilkinson, Special Database 3: Handwritten Segmented Characters. Technical Report, National Institute of Standards and Technology (1992).