Multiresolution recognition of unconstrained handwritten numerals with wavelet transform and multilayer cluster neural network

Pattern Recognition

Volumn 29, Issue 12, 1996, Pages 1953-1961

  Lee, Seong Whan ^a,d,e,f   Kim, Chang Hun ^a   Ma, Hong ^b   Tang, Yuan Y ^c  

^a Korea University   (South Korea)

^b SICHUAN UNIVERSITY   (China)

^c HONG KONG BAPTIST UNIVERSITY   (Hong Kong)

^d DELFT UNIVERSITY OF TECHNOLOGY   (Netherlands)

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

^f Chungbuk National University   (South Korea)

Author keywords

Handwritten numeral recognition; Multilayer cluster neural network; Multiresolution recognition; Wavelet transform

Indexed keywords

CLASSIFICATION (OF INFORMATION); ERROR ANALYSIS; NEURAL NETWORKS; PERFORMANCE; WAVELET TRANSFORMS;

HANDWRITTEN NUMERAL RECOGNITION; MULTILAYER CLUSTER NEURAL NETWORK; MULTIRESOLUTION RECOGNITION;

OBJECT RECOGNITION;

EID: 0030410516     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0031-3203(96)00053-2     Document Type: Article

References (18)

1. S. G. Mallat, A theory for multiresolution signal decomposition: The wavelet representation, IEEE Trans. Pattern Anal. Mach. Intell. 11(7), 674-693 (1989).
2. C. K. Chui, An Introduction to Wavelets. Academic Press, Boston (1992).
3. A. Haar, Zur Theorie der orthogonalen Funktionen-system, Math. Analysis 69, 331-371 (1910).
4. C. Nadal and C. Y. Suen, Recognition of totally unconstrained handwritten digit by decomposition and vectorization, Technical Report, Concordia University, Montreal, Canada (1988).
5. L. Lam and C. Y. Suen, Structural classification and relaxation matching of totally unconstrained handwritten ZIP-code numbers, Pattern Recognition 21(1), 19-31 (1988).
6. T. Mai and C.Y. Suen, A generalized knowledge-based system for the recognition of unconstrained handwritten numerals, IEEE Trans. Syst. Man Cybernet. 20(4), 835-848 (1990).
7. R. Legault and C. Y. Suen, Contour tracing and parametric approximations for digitized patterns, Computer Vision and Shape Recognition, A. Krzyzak, T. Kasvand and C. Y. Suen, eds. pp. 225-240. World Scientific Publishing, Singapore (1989).
8. C. Y. Suen, C. Nadal, T. A. Mai, R. Legault and L. Lam, Recognition of handwritten numerals based on the concept of multiple experts, Proc. 1st Int. Workshop on Frontiers in Handwriting Recognition, Montreal, Canada, 131-144 (1990).
9. K. Fukushima, Neocognitron: A hierarchical neural network capable of visual pattern recognition, Neural Networks 1(2), 119-130 (1988).
10. A. Krzyzak, W. Dai and C. Y. Suen, Unconstrained handwritten character classification using modified backpropagation model, Proc. 1st Int. Workshop on Frontiers in Handwriting Recognition, Montreal, Canada, 155-166 (1990).
11. Y. Le Cun et al., Constrained neural network for unconstrained handwritten digit recognition, Proc. 1st Int. Workshop on Frontiers in Handwriting Recognition, Montreal, Canada, 145-154 (1990).
12. S. Knerr, L. Personnaz and G. Dreyfus, Handwritten digit recognition by neural networks with single-layer training, IEEE Trans. Neural Networks 3(6) 962-968 (1992).
13. P. Wunsch and A. F. Laine, Wavelet descriptors for multiresolution recognition of handprinted characters, Pattern Recognition 28(8), 1237-1249 (1995).
14. Y. Y. Tang, H. Ma, D. Xi, Y. Cheng and C. Y. Suen, Extraction of reference lines from document with greylevel background using sub-image of wavelets, Proc. 3rd Int. Conf. on Document Analysis and Recognition, Montreal, Canada, 571-574 (1995).
15. 2(R), Trans. Amer. Math. Soc. 315(1), 69-87 (1989).
16. D. E. Rumelhart, G. E. Hinton and R. J. Williams, Learning internal representations by error propagation, Parallel Distributed Processing, D. E. Rumelhart and J. L. McClelland, eds. pp. 318-362, MIT Press, Cambridge (1986).
17. Y. Le Cun, Generalization and network design strategies, Connectionism in Perspective, R. Pfeifer, Z. Schreter, F. Fogelman and L. Steels, eds. Elsevier, Zurich, Switzerland (1989).
18. H. Drucker, R. Schapire and P. Simard, Boosting performance in neural networks, Int. J. Pattern Recognition Artific. Intell. 7(4), 61-75 (1993).