A neuro-fuzzy inference engine for Farsi numeral characters recognition

Expert Systems with Applications

Volumn 37, Issue 9, 2010, Pages 6327-6337

  Montazer, Gholam Ali ^a   Saremi, Hamed Qahri ^b   Khatibi, Vahid ^a  

^a TARBIAT MODARES UNIVERSITY   (Iran)

^b MCMASTER UNIVERSITY   (Canada)

Author keywords

Character recognition; Farsi numbers; Fuzzy rules; Multi layer perceptron neural network; Neuro fuzzy inference engine

Indexed keywords

CHARACTER RECOGNITION; DEEP NEURAL NETWORKS; ENGINES; FUZZY NEURAL NETWORKS; FUZZY RULES; FUZZY SET THEORY; LEARNING SYSTEMS; NETWORK LAYERS; NEURAL NETWORKS;

ARABIC TEXTS; FARSI NUMBERS; HOLISTIC APPROACH; MACHINE LEARNING METHODS; MAMDANI INFERENCE; MULTI-LAYER PERCEPTRON NEURAL NETWORKS; NEURO-FUZZY;

FUZZY INFERENCE;

EID: 78951489145     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2010.02.088     Document Type: Article

References (41)

1. AI-Alawi, R. (2004). A hybrid n-tuple neuro-fuzzy classifier for handwritten numerals recognition. Paper presented at the IEEE international joint conference on neural networks, Budapest, Hungary.
2. Al-Muhtaseb, H. A., Mahmoud, S. A., & Qahwaji, R. S. (2008). Recognition of off-line printed Arabic text using hidden Markov models. Signal Processing, 88(12), 2902-2912.
3. Al-Omari, F. A., & Al-Jarrah, O. (2004). Handwritten Indian numerals recognition system using probabilistic neural networks. Advanced Engineering Informatics, 18(1), 9-16.
4. Amin, A. (2000). Recognition of printed Arabic text based on global features and decision tree learning techniques. Pattern Recognition, 33(8), 1309-1323.
5. Amor, N. B., & Amara, N. E. B. (2005). Multifont Arabic character recognition using Hough transform and hidden Markov models. Paper presented at the fourth international symposium on image and signal processing and analysis, Zagreb, Croatia.
6. Azmi, R., & Kabir, E. (2001). A new segmentation technique for omnifont Farsi text. Pattern Recognition Letters, 22, 97-104. (Pubitemid 32214716)
7. Baghshah, M. S., Shouraki, S. B., & Kasaei, S. (2005). A novel fuzzy approach to recognition of online Persian handwriting. Paper presented at the 5th international conference on intelligent systems design and applications, Wroclaw, Poland.
8. Broumandnia, A., & Shanbehzadeh, J. (2007). Fast Zernike wavelet moments for Farsi character recognition. Image and Vision Computing, 25, 717-726.
9. Bunke, H., Roth, M., & Schukat-Talamazzini, E. (1995). Off-line cursive handwriting recognition using hidden Markov models. Pattern Recognition, 28, 1399-1413.
10. Camastra, F. (2007). A SVM-based cursive character recognizer. Pattern Recognition, 40(12), 3721-3727. (Pubitemid 47223273)
11. Cheok, A. D., Jian, Z., & Chng, E. S. (2008). Efficient mobile phone Chinese optical character recognition systems by use of heuristic fuzzy rules and bigram Markov language models. Applied Soft Computing, 8(2), 1005-1017. (Pubitemid 350266495)
12. Chi, Z., Suters, M., & Yan, H. (1996). Handwritten digit recognition using combined ID3-derived fuzzy rules and Markov chains. Pattern Recognition, 29(11), 1821-1833. (Pubitemid 126383971)
13. Dehghan, M., Faez, K., Ahmadi, M., & Shridhar, M. (2001). Unconstrained Farsi handwritten word recognition using fuzzy vector quantization and hidden Markov models. Pattern Recognition Letters, 2001, 209-214. (Pubitemid 32207839)
14. Dimauro, G., Impedovo, S., Pirlo, G., & Salzo, A. (1997). Automatic banckcheck processing: A new engineered system. International Journal of Pattern Recognition and Artificial Intelligence, 467-503.
15. Fang, X., & Alouani, A. T. (2002). Unconstrained Handritten Numeral Recognition Using Fuzzy Rule-Based Classification. Paper presented at the 34th Southeastern symposium on system theory, Huntsville, Alabama.
16. Goltsev, A., & Rachkovskij, D. (2005). Combination of the assembly neural network with a perceptron for recognition of handwritten digits arranged in numeral strings. Pattern Recognition, 38(3), 315-322.
17. Hanmandlua, M., Mohanb, K. R. M., Chakrabortyc, S., & Goyald, S. (2003). Unconstrained handwritten character recognition based on fuzzy logic. Pattern Recognition, 36(603-623).
18. Ho, B., & Leedham, G. (2001). Off-line constrained vocabulary cursive script recognition using visible features. Paper presented at the 7th Australian and New Zealand intelligent information systems conference, Perth, Western Australia.
19. Hung, K.-Y., Luk, R. W. P., Yeung, D. S., Chung, K. F. L., & Shu, W. (2005). A multiple classifier approach to detect Chinese character recognition errors. Pattern Recognition, 38(5), 723-738. (Pubitemid 40226365)
20. Itoh, N. (1995). Japanese language model based on bigrams and its application to on-line character recognition. Pattern Recognition, 28(2), 135-141.
21. Khorsheed, M. S. (2003). Recognising handwritten Arabic manuscripts using a single hidden Markov model. Pattern Recognition Letters, 24(14), 2235-2242. (Pubitemid 36911068)
22. Kimura, F., Wakabayashi, T., Tsuruoka, S., & Miyake, Y. (1997). Improvement of handwritten Japanese character recognition using weighted direction code histogram. Pattern Recognition, 30(8), 1329-1337. (Pubitemid 127417901)
23. Lauer, F., Suen, C. Y., & Bloch, G. (2007). A trainable feature extractor for handwritten digit recognition. Pattern Recognition, 40(6), 1816-1824. (Pubitemid 46402919)
24. Li, Y.-X., Tan, C. L., Ding, X., & Liu, C. (2004). Contextual post-processing based on the confusion matrix in offline handwritten Chinese script recognition. Pattern Recognition, 37(9), 1901-1912. (Pubitemid 38804476)
25. Malon, C., Uchida, S., & Suzuki, M. (2008). Mathematical symbol recognition with support vector machines. Pattern Recognition Letters, 29(9), 1326-1332.
26. Mamdani, E. H. (1976). Advances in the linguistic synthesis of fuzzy controllers. International Journal of Man-Machine Studies, 8(6), 669-678.
27. Mitchell, P. E., & Yan, H. (2004). Newspaper layout analysis incorporating connected component separation. Image and Vision Computing, 22, 307-317.
28. Montazer, G. A., & Jafari, N. (2006). Design a fuzzy recognition system for Persian numeral fonts based on fuzzy grammar concepts. WSEAS Transactions on Electronics, 3(10), 511-518. (Pubitemid 46916562)
29. Morita, M. E., Lethelier, E., Yacoubi, A. E., Bortolozzi, F., Sabourin, R., & Pontifícia, P. (2000). Recognition of handwritten dates on bankchecks using an HMM approach. Paper presented at the 13th Brazilian symposium on computer graphics and image processing, Gramado, Brazil.
30. Mozaffari, S., Faez, K., Märgner, V., & El-Abed, H. (2008). Lexicon reduction using dots for off-line Farsi/Arabic handwritten word recognition. Pattern Recognition Letters, 29(6), 724-734.
31. Nagabhushan, P., & Pai, R. M. (1999). Modified region decomposition method and optimal depth decision tree in the recognition of non-uniform sized characters - An experimentation with Kannada characters. Pattern Recognition Letters, 20(14), 1467-1475. (Pubitemid 30545396)
32. Pal, U., & Chaudhuri, B. B. (2004). Indian script character recognition: A survey. Pattern Recognition, 37(9), 1887-1899. (Pubitemid 38804475)
33. Pan, X., Ye, X., & Zhang, S. (2005). A hybrid method for robust car plate character recognition. Engineering Applications of Artificial Intelligence, 18(8), 963-972. (Pubitemid 41455088)
34. Patil, P. M., & Sontakke, T. R. (2007). Rotation, scale and translation invariant handwritten Devanagari numeral character recognition using general fuzzy neural network. Pattern Recognition, 40(7), 2110-2117. (Pubitemid 46522462)
35. Ping, Z., & Lihui, C. (2002). A novel feature extraction method and hybrid tree classification for handwritten numeral recognition. Pattern Recognition Letters, 23(1-3), 45-56.
36. Solimanpour, F., Sadri, J., & Suen, C. Y. (2006). Standard databases for recognition of handwritten digits, numerical strings, legal amounts, letters and dates in Farsi language. Paper presented at the 10th Int'l workshop on frontiers of handwriting recognition, La Baule, France.
37. Srihari, S. N., Hong, T., & Srikantan, G. (1997). Machine-printed Japanese document recognition. Pattern Recognition, 30(8), 1301-1313. (Pubitemid 127417898)
38. Su, T.-H., Zhang, T.-W., Guan, D.-J., & Huang, H.-J. (2009). Off-line recognition of realistic Chinese handwriting using segmentation-free strategy. Pattern Recognition, 42(1), 167-182.
39. Theeramunkong, T., & Wongtapan, C. (2005). Off-line isolated handwritten Thai OCR using island-based projection with n-gram model and hidden Markov models. Information Processing and Management, 41(1), 139-160.
40. Zhao, S., Chi, Z., Shi, P., & Yan, H. (2003). Two-stage segmentation of unconstrained handwritten Chinese characters. Pattern Recognition, 36(1), 145-156.
41. Ziaratban, M., Faez, K., & Faradji, F. (2007). Language-based feature extraction using template-matching in Farsi/Arabic handwritten numeral recognition. Paper presented at the 9th int'l conference on document analysis and recognition, Curitiba, Brazil.