Efficient mobile phone Chinese optical character recognition systems by use of heuristic fuzzy rules and bigram Markov language models

Applied Soft Computing Journal

Volumn 8, Issue 2, 2008, Pages 1005-1017

  Cheok, Adrian David ^a   Jian, Zhang ^b   Chng, Eng Siong ^c  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^b Sony Electronics Asia Pacific Pte Ltd   (Singapore)

^c NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

Fuzzy logic; Heuristic; Markov model; Statistical language model

Indexed keywords

COMPUTATIONAL COMPLEXITY; HEURISTIC METHODS; HIDDEN MARKOV MODELS; MATHEMATICAL MODELS; MOBILE PHONES; SEMANTICS;

BIGRAM MARKOV LANGUAGE MODELS; CRISP RECOGNITION SYSTEMS; LINGUISTIC RULES; OPTICAL CHARACTER RECOGNITION SYSTEMS; POCKET COMPUTERS; STATISTICAL LANGUAGE MODELS;

FUZZY RULES;

EID: 37249031001     PISSN: 15684946     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asoc.2007.02.013     Document Type: Article

References (26)

1. Hahn S.H., Lee J.H., and Kim J.H. A Study on Utilizing OCR Technology in Building Text Database (1999) pp. 582-586
2. Chuang C.T., and Tseng L.Y. A stroke extraction method for multifont Chinese characters based on the reduced special interval graph. IEEE Trans. Syst. Man Cybernet. 25 7 (1995) 1171-1178
3. Masa P., Heim P., Franzi E., Arreguit X., Heitger F., Ruedi P., Nuss-baum P., Piiloud P., and Vittoz E. 10 mW cmos retina and classifier for handheld, 1000 images/s optical character recognition system. Proceedings of the 1999 IEEE International Solid-State Circuits Conference (1999) 204-205
4. Wong P.K., and Chan C. Postprocessing statistical language models for a handwritten Chinese character recognizer. IEEE Trans. Syst. Man Cybernet., Part B 29 (1999) 286-291
5. Wong P.K., and Chan C. Off-line handwritten Chinese character recognition as a compound Bayes decision problem. IEEE Trans. Pattern Anal. Mach. Intell. 20 (1998) 1016-1023
6. Lee H.J., Tung C.H., and Chang Chien C.H. A Markov model in handwritten Chinese text recognition. Proceedings of 2nd International Conference on Document Analysis and Recognition. Tsukuba Japan (1993) pp. 72-75
7. Liao T.W., Celmins A.K., Robert I., and Hammell J. A fuzzy c-means variant for the generation of fuzzy term sets. Fuzzy Sets Syst. 135 2 (2003) 241-257
8. Gao J., Wang H.F., Li M., and Lee K.-F. A unified approach to statistical language modeling for Chinese. IEEE International Conference on Acoustics, Speech, and Signal Processing. June (2000) 1703-1706
9. Bin T., Jun C., Kechu Y., and Hui W. A Chinese word dividing algorithm based on statistical language models. Proceedings of IEEE ICSP '96 (1996) 805-808
10. Juang B.H., and Furui S. Automatic recognition and understanding of spoken language-a first step toward natural human-machine communication. Proc. IEEE 88 (2000) 1142-1165
11. Ortmanns S., Ney H., and Eiden A. Language-model look-ahead for large vocabulary speech recognition. Proceedings of Fourth International Conference on Spoken Language Processing, ICSLP '96, vol. 4 (1996) 2095-2098
12. Doster W. Contextual postprocessing system for cooperation with a multiple choice character recognition system. IEEE Trans. Comput. 26 (November 1977) 1090-1101
13. Yannakoudakis E.J., Tsomokos I., and Hutton P.J. N-Grams and their implication to natural language understanding. Pattern Recogn. 23 (May 1990) 509-528
14. Bellegarda J.R. A statistical language modeling approach integrating local and global constraints. 1997 IEEE Workshop on Automatic Speech Recognition and Understanding Proceedings (1997) 262-269
15. Lee L.S. Golden Mandarin (II)-an intelligent mandarin dictation machine for Chinese character input with adaptation/learning functions. Proceedings of 1994 International Symposium on Speech, Image Processing and Neural Networks. Hong Kong, 13-16 April (1994)
16. Paul D.B., Baker J.K., and Baker J.M. On the interaction between true source, training, and testing language models. Proceedings of the 1991 International Conference on Acoustics, Speech and Signal Processing, ICASSP '91 (Cat. No. 91CH2977-7), vol. 1 (1991) 569-572
17. Clark J.L., Lua K.T., and McCallum J. Conformance of Chinese text to Zipf's law. IEEE International Conference on Databases, Parallel Architectures and their Applications. March (1990) 533
18. Tung C.H., and Lee H.J. 2-stage character recognition by detection and correction of erroneously-identified characters. Proceedings of Second International Conference on Document Analysis and Recognition (ICDAR '93) (1993) 834-837
19. Larsen H.L., and Yager R.R. A framework for fuzzy recognition technology. IEEE Trans. Syst. Man Cybernet., Part C: Appl. Rev. 30 (2000) 65-76
20. Yager R.R. Fuzzy modeling for intelligent decision making under uncertainty. IEEE Trans. Syst. Man Cybernet., Part B 30 (2000) 60-70
21. Boston J.R. A signal detection system based on Dempster-Shafer theory and comparison to fuzzy detection. IEEE Trans. Syst. Man Cybernet., Part C: Appl. Rev. 30 (2000) 45-51
22. Rubin S.H. Computing with words. IEEE Trans. Syst. Man Cybernet., Part B 29 (1999) 518-524
23. Wang X.Z., Yeung D.S., and Tsang E.C.C. A comparative study on heuristic algorithms for generating fuzzy decision trees. IEEE Trans. Syst. Man Cybernet., Part B 31 (April 2001) 215-226
24. Voit G. Fuzzy logic in c. Dr. Dobbs J. (1993) 40-49
25. Lea R., and Kreinovich V. Intelligent control makes sense even without expert knowledge: an explanation. APIC '95 (A Supplement to the International Journal of Reliable Computing) (1995)
26. Natarajan P., Bazzi I., Lu Z., Makhoul J., and Scwhartz R. Robust OCR of degraded documents. IEEE Proceedings of the Fifth International Conference on Document Analysis and Recognition. September (1999) 357-361