A new hybrid approach in combining multiple experts to recognise handwritten numerals

Pattern Recognition Letters

Volumn 18, Issue 8, 1997, Pages 781-790

  Rahman, A F R ^a   Fairhurst, M C ^a  

^a UNIVERSITY OF KENT   (United Kingdom)

Author keywords

Computer vision; Hand written numeral recognition; Multiple expert classifier

Indexed keywords

COMPUTER VISION; DECISION THEORY;

HANDWRITTEN NUMERAL RECOGNITION; MULTIPLE EXPERT CLASSIFIER;

OPTICAL CHARACTER RECOGNITION;

EID: 0031197672     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0167-8655(97)00078-0     Document Type: Article

References (32)

1. Cao, J., Ahmadi, M., Shridhar, M., 1995. Recognition of handwritten numerals with multiple feature and multistage classifier. Pattern Recognition 28 (2), 153.
2. Chi, Z., Wu, J., Yan, H., 1995. Handwritten numeral recognition using self-organising maps and fuzzy rules. Pattern Recognition 28 (1), 59.
3. Duerr, B., Haettich, W., Tropf, H., Winkler, G., 1980. A combination of statistical and syntactical pattern recoognition applied to classification of unconstrained handwritten numerals. Pattern Recognition 12, 189-199.
4. Errico, G.D., Dimauro, G., Impedovo, S., Pirlo, G., 1996. A new multi-expert system for handwritten digit recognition. In: Proc. 5th Internat. Workshop on Frontiers of Handwriting Recognition, pp. 341-344.
5. Fairhurst, M.C., Mattaso Maia, M.A.G., 1986. Performance comparison in hierarchical architectures for memory network pattern classifiers. Pattern Recognition Letters 4 (2), 121.
6. Frank, J., Mandler, E., 1992. A comparison of two approaches for combining the votes of cooperating classifiers. In: Proc. 11th ICPR, The Hague, The Netherlands, pp. 611-614.
7. Haralick, R.M., 1976. The table look-up rule. Comm. Statist. Theory Methods A 5 (12), 1163.
8. Ho, T.K., 1996. Adaptive coordination of multiple classifiers. In: Proc. Internat. Workshop on Document Analysis Systems, Malvern, PA, pp. 338-351.
9. Ho, K.H., Hull, J.J., Srihari, S.N., 1992. Combination of decisions by multiple classifiers in structured document image analysis. In: Baird, H.S., Bunke, H., Yamamoto, K. (Eds.), S-V, pp. 188-202.
10. Ho, T.K., Hull, J.J., Srihari, S.N., 1994. Decision combination in multiple classifier systems. IEEE Trans. Pattern Anal. Machine Intell. 16 (1), 66.
11. Huang, Y.S., Suen, C.Y., 1995. A method of combining multiple experts for the recognition of unconstrained handwritten numerals. IEEE Trans. Pattern Anal. Machine Intell. 17 (1), 90.
12. Hull, J.J., Commike, A.A., Ho, T.K., 1990. Multiple algorithms for handwritten character recognition. In: Proc. 1st Internat. Workshop on Frontiers in Handwriting Recognition, Montréal, Canada, pp. 117-124.
13. Jones, M.A., Story, G.A., Ballard, B.W., 1991. Integrating multiple knowledge sources in a bayesian ocr post-processor. In: Proc. 1st Internat. Conf. on Document Analysis and Recognition, Saint-Malo, France, pp. 925-933.
14. Kimura, F., Shridhar, M., 1991. Handwritten numeral recognition based on multiple algorithms. Pattern Recognition 24 (10), 969.
15. Kittler, J., Hatel, M., 1996. Improving recognition rates by classifier combination. In: Proc. 5th Internat. Workshop on Frontiers of Handwriting Recognition, pp. 81-102.
16. Kovács, Zs.M., Ragazzoni, R., Rovatti, R., Guerrieri, R., 1993. Improved handwritten character recognition using second-order information from training set. Electronics Letters 29 (14), 1308.
17. Lam, L., Suen, C.Y., 1994. A theoretical-analysis of the application of majority voting to pattern-recognition. In: Proc. 12th IAPR Int. Conf. on Pattern Recognition, Conf. B: Pattern Recognition and Neural Networks, vol. 2, Jerusalem, Israel, 1994, pp. 418-420.
18. Mazurov, V.D., Krivonogov, A.I., Kazantsev, V.L., 1987. Solving of optimisation and identification problems by the committee methods. Pattern Recognition 20 (4), 371.
19. Nadal, C., Legault, R., Suen, C.Y., 1990. Complementary algorithms for the recognition of totally unconstrained handwritten numerals. In: Proc. 10th ICPR, Atlantic City, NJ, pp. 443-449.
20. Portegys, T.E., 1995. A search technique for pattern recognition using relative distances. IEEE Trans. Pattern Anal. Machine Intell. 17 (9), 910.
21. Powalka, R.K., Sherkat, N., Whitrow, R.J., 1996. Multiple recognizer combination topologies. In: Simner, M.L., Leedham, C.G., Thomassen, A.J.W.M. (Eds.), Handwriting and Drawing Research: Basic and Applied Issues. IOC Press, pp. 329-342.
22. Rahman, A.F.R., 1996. Internal Report. Image Processing & Computer Vision Group, Electronic Engineering, University of Kent, Canterbury, CT2 7NT, UK.
23. Rahman, A.F.R., Fairhurst, M.C., 1997. Selective partition algorithm for finding regions of maximum pairwise dissimilarity among statistical class models. Pattern Recognition Lett. 18 (7), 605-611.
24. Reiss, T.H., 1993. Recognizing Planer Objects Using Invariant Image Features. Springer, Berlin.
25. Rumelhart, D.E., Hinton, G.E., Williams, R.J., 1986. Learning internal representations by error propagation. In: Rumelhart, D.E., McClelland, J.L. (Eds.), Parallel Distributed Processing, vol. 1. MIT Press, Cambridge, MA, pp. 318-362.
26. Shafer, G., Logan, R., 1987. Implementing dempster's rule for hierarchical evidence. Artifical Intelligence 33, 271-298.
27. Suen, C.Y., Nadal, C., Mai, T.A., Legault, R., Lam, L., 1990. Recognition of totally unconstrained handwritten numerals based on the concept of multiple experts. In: Proc. IWFHR, Montréal, Canada, pp. 131-143.
28. Suen, C.Y., Nadal, C., Legault, R., Mai, T.A., Lam, L., 1992. Computer recognition of unconstrained handwritten numerals. Proc. IEEE 80 (7), 1162.
29. Vasconcelos, G.C., Fairhurst, M.C., Bisset, D.L., 1995. Efficient detection of spurious inputs for improving the robustness of mlp networks in practical applications. Neural Comput. Appl. 3, 202.
30. Wu, Q.Z., Jou, I.C., Lecunn, Y., 1995. A pyramid multiresolution classifier for online large vocabulary Chinese character-recognition. In: Proc. SPIE Conf. on Visual Communications and Imaging Processing, Taipei, Taiwan, vol. 2501, pp. 158-165.
31. Xu, L., Krzyzak, A., Suen, C.Y., 1992. Methods of combining multiple classifiers and their applications to handwriting recognition. IEEE Trans. Systems Man Cybernet. 23 (3), 418.
32. Zhou, J., Pavlidis, T., 1994. Discrimination of characters by a multi-stage recognition process. Pattern Recognition 27 (11), 1539.