A Generalized Knowledge-Based System for the Recognition of Unconstrained Handwritten Numerals

IEEE Transactions on Systems, Man and Cybernetics

Volumn 20, Issue 4, 1990, Pages 835-848

  Mai, Tuan A ^a   Suen, Ching Y ^a  

^a Gina Cody School of Engineering and Computer Science   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

EXPERT SYSTEMS--KNOWLEDGE BASES; PROBABILITY;

HANDWRITTEN NUMERALS RECOGNITION; RECOGNITION/REJECTION TRADEOFF; UNCONSTRAINED HANDWRITTEN NUMERALS;

CHARACTER RECOGNITION;

EID: 0025458421     PISSN: 00189472     EISSN: 21682909     Source Type: Journal    
DOI: 10.1109/21.105083     Document Type: Article

References (14)

1. P. Ahmed and C. Y. Suen, “Computer recognition of totally unconstrained handwritten Zip codes,” Int. J. Pattern Recog. Artificial Intell., vol. 1, no. 1, pp. 1–15, 1987.
2. M. Beun, “A flexible method for automatic reading of handwritten numerals,” Philips Tech. Reu., vol. 33, pp. 89–101, 130–137, 1973.
3. B. Duerr, W. Haettich, H. Trof, and G. Winkler, “A combination of statistical and syntactical pattern recognition applied to classification of unconstrained handwritten numerals,” Pattern Recog., vol. 12, pp. 189–199, 1980.
4. J. J. Hull, S. N. Srihari, E. Cohen, C. L. Kuan, P. Cullen, and P. Palumbo, “A blackboard-based approach to handwritten Zip code recognition,” Proc. U.S. Postal Service Advanced Technology Conf. 3, pp. 1018–1032, 1988.
5. F. A. Kamangar and M. J. Cykana, “Recognition of handwritten numerals using a multilayer neural network,” in Proc. U.S. Postal Service Advanced Technology Conf. 3, pp. 768–781, 1988.
6. C. L. Kuan and S. N. Srihari, “A stroke-based approach to handwritten numeral recognition,” in Proc. U.S. Postal Service Advanced Technology Conf. 3, pp. 1033–1041, 1988.
7. L. Lam and C. Y. Suen, “Structural classification and relaxation matching of totally unconstrained handwritten numerals,” Pattern Recog., vol. 21, no. 1, pp. 19–31, 1988.
8. T. Mai, “A knowledge-based approach to recognize unconstrained handwritten numerals,” master thesis in computer science, Concordia University, Montreal, PQ, Canada, 1989.
9. J. Mantas, “Methodologies in pattern recognition and image analysis—A brief survey,” Pattern Recog., vol. 20, pp. 1–6, 1987.
10. B. T. Mitchell and A. M. Gillies, “Advanced research in recognizing handwritten ZIP codes,” in Proc. U.S. Postal Service Advanced Technology Conf. 3, pp. 813–827, 1988.
11. N. J. Naccache and R. Shinghal, “An investigation into the skeletonization approach of Hilditch,” Pattern Recog., vol. 17, pp. 279–284, 1984.
12. T. F. Pawlicki, D. Lee, J. J. Hull and S. N. Srihari, “Neural network models and their application to handwritten digit recognition,” Proc. U.S. Postal Service Advanced Technology Conf. 3, pp. 751–767, 1988.
13. C. Y. Suen, P. Ahmed and L. Lam, “Recognition of totally unconstrained handwritten Zip codes,” in Proc. U.S. Postal Service Advanced Technology Conf. 3, pp. 885–886, 1988.
14. C. Y. Suen, “Distinctive features in the automatic recognition of handprinted characters,” Signal Processing 4, pp. 193–207, 1982.