Handwritten Bangla numeral recognition system and its application to postal automation

Pattern Recognition

Volumn 40, Issue 1, 2007, Pages 99-107

  Wen, Ying ^a,b   Lu, Yue ^b,c   Shi, Pengfei ^a  

^a SHANGHAI JIAO TONG UNIVERSITY   (China)

^b EAST CHINA NORMAL UNIVERSITY   (China)

^c Shanghai Research Institute of Postal Science   (China)

Author keywords

Bangla numeral recognition; Feature extraction; Principal component analysis; Support vector machine

Indexed keywords

FEATURE EXTRACTION; IMAGE RECONSTRUCTION; LEARNING SYSTEMS; PRINCIPAL COMPONENT ANALYSIS;

AUTOMATIC LETTER SORTING MACHINE; BANGLA NUMERAL RECOGNITION; INTEGRATED SYSTEM; SUPPORT VECTOR MACHINE;

PATTERN RECOGNITION SYSTEMS;

EID: 33749241176     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2006.07.001     Document Type: Article

References (23)

1. Chaudhuri B.B., and Pal U. A complete printed Bangla OCR system. Pattern Recognition 31 (1998) 531-549
2. U. Pal, On the development of an optical character recognition (OCR) system for printed Bangla script, Ph.D. Thesis, 1997.
3. Pal U., and Chaudhuri B.B. Indian script character recognition: a survey. Pattern Recognition 37 (2004) 1887-1899
4. Pal U., and Chaudhuri B.B. Automatic recognition of unconstrained off-line Bangla hand-written numerals. In: Tan T., Shi Y., and Gao W. (Eds). Advances in Multimodal Interfaces, Lecture Notes in Computer Science vol. 1948 (2000), Springer, Berlin 371-378
5. Roy K., Vajda S., Pal U., and Chaudhuri B.B. A system towards Indian postal automation. Proceedings of the Ninth International Workshop on Frontiers in Handwritten Recognition (IWFHR-9 2004) (October 2004) 580-585
6. Pal U., Belad A., and Choisy Ch. Touching numeral segmentation using water reservoir concept. Pattern Recognition Lett. 24 (2003) 261-272
7. Kim I.-J., and Kinm J.-H. Statistical character structure modeling and its application to handwritten Chinese character recognition. IEEE Trans. Pattern Anal. Mach. Intell. 25 11 (2003) 1422-1436
8. 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 9 (1998) 1016-1023
9. Cheung K.-W., Yeung D.-Y., and Chin R.T. A Bayesian framework for deformable pattern recognition with application to handwritten character recognition. IEEE Trans. Pattern Anal. Mach. Intell. 20 12 (1998) 1382-1388
10. Govindaraju V., Slavik P., and Xue H. Use of Lexicon density in evaluating word recognizers. IEEE Trans. Pattern Anal. Mach. Intell. 24 6 (2002) 789-800
11. Madhvanath S., Kim G., and Govindaraju V. Chaincode contour processing for handwritten word recognition. IEEE Trans. Pattern Anal. Mach. Intell. 21 9 (1999) 928-932
12. Twining C.J., and Taylor C.J. The use of kernel principal component analysis to model data distributions. Pattern Recognition 36 (2003) 217-227
13. Kim H.-C., Kim D., and Bang S.Y. A numeral character recognition using the PCA mixture model. Pattern Recognition Lett. 23 (2002) 103-111
14. Partridge M., and Calvo R.A. Fast dimensionality reduction and simple PCA. Intell. Data Anal. 2 (1998) 203-214
15. Yang J., Zhang D., Frangi, et al. Two-dimensional PCA: a new approach to appearance-based face representation and recognition. IEEE Trans. Pattern Anal. Mach. Intell. 26 1 (2004) 131-137
16. Scholkopf B., Smola A., and Muller K.R. Nonlinear component analysis as a kernel eigenvalue problem. Neural Comput. 10 (1998) 1299-1319
17. Liang Z., and Shi P.F. Uncorrelated discriminant vector using a kernel method. Pattern Recognition 38 (2005) 307-310
18. Liang Z., and Shi P.F. Kernel direct discriminant analysis and its theoretical foundation. Pattern Recognition 38 (2005) 445-447
19. Vapnik V.N. The Nature of Statistical Learning Theory (1995), Springer, New York
20. JolliHe I.J. Principal Component Analysis (1986), Springer, New York
21. Dong J.-X., Krzyzak A., and Suen C.Y. Fast SVM training algorithm with decomposition on very large data sets. IEEE Trans. Pattern Anal. Mach. Intell. 27 4 (2005) 603-618
22. Lee S.W. Off-line recognition of totally unconstrained handwritten numerals using multilayer cluster neural network. IEEE Trans. Pattern Anal. Mach. Intell. 18 6 (1996) 648-652
23. Pratt W.K. Digital Image Processing (1978), Wiley, New York