Evaluating a zoning mechanism and class-modular architecture for handwritten characters recognition

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4756 LNCS, Issue , 2007, Pages 515-524

  De Avila, Sandra ^a   Matos, Leonardo ^a   Freitas, Cinthia ^b   De Carvalho, João M ^c  

^a FEDERAL UNIVERSITY OF SERGIPE   (Brazil)

^b PONTIFICAL CATHOLIC UNIVERSITY OF PARANÁ   (Brazil)

^c FEDERAL UNIVERSITY OF CAMPINA GRANDE   (Brazil)

Author keywords

Class modular architecture; Directional histogram; Handwritten characters recognition

Indexed keywords

COMPUTER ARCHITECTURE; DATABASE SYSTEMS; NEURAL NETWORKS; PROBLEM SOLVING;

CLASS-MODULAR ARCHITECTURE; DIRECTIONAL HISTOGRAM; HANDWRITTEN CHARACTERS RECOGNITION;

CHARACTER RECOGNITION;

EID: 38449094107     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-76725-1_54     Document Type: Conference Paper

References (14)

1. Cormack, L.K., Bovik, A.I.: Computation models of early human vision in Handbook of image and video processing, p. 891. Academic Press, San Diego (2000)
2. Freitas, C.O.A., Oliveira, L.E.S., de Bortolozzi, F., Aires, S.B.K.: Handwritten character recognition using non-symmetrical perceptual zoning. International Journal of Pattern Recognition and Artificial Intelligence 21, 1-21 (2007)
3. Kapp, M.N., Freitas, C.O.A., Sabourin, R.: Methodology for the design of NN-based month-word recognizers written on brazilian bank checks. International Journal of Image and Vision Computing, Image and Vision Computing 25, 40-49 (2007)
4. Matos, L.N.: Utilização de redes bayesianas como agrupador de classificadores locais e global. PhD thesis, Federal University of Campina Grande, Brazil (2004)
5. Newman, D.J., Hettich, S., Blake, C.L., Merz, C.J.: UCI repository of machine learning databases, Irvine, CA: University of California, Department of Information and Computer Science (1998)
6. Oh, I.-S., Suen, C.Y.: A class-modular feedforward neural network for handwriting recognition. Pattern Recognition 35(1), 229-244 (2002)
7. Poisson, E., Viard-Gaudin, C., Lallican, P.M.: Multi-modular architecture based on convolutional neural networks for online handwritten character recognition. In: IEEE Proceedings of the 9th International Conference on Neural Information Processing, vol. 5, pp. 2444-2448 (2002)
8. Principe, J.C., Euliano, N.R., Lefebvre, W.C.: Neural and adaptive systems: fundamentals through simulations. John Wiley & Sons, New York, USA (1999)
9. Rifkin, R., Klautau, A.: In defense of one-vs-all classification. The Journal of Machine Learning Research 5, 101-141 (2004)
10. Shi, M., Fujisawa, Y., Wakabayashi, T., Kimura, F.: Handwritten numeral recognition using gradient and curvature of grayscale image. Pattern Recognition 35(10), 2051-2059 (2002)
11. Suen, C.Y., Guo, J., Li, Z.C.: Analysis and recognition of alphanumeric handprints by parts. IEEE Transactions on Systems, Man and Cybernetics 24(4), 614-631 (1994)
12. Trier, O., Jain, A., Taxt, T.: Feature extraction methods for character recognition - a survey. Pattern Recognition 29(4), 641-662 (1996)
13. Viard-Gaudin, C., Lallican, P.M., Binter, P., Knerr, S., The, I.R.E.S.T.E.: on/off IRONOFF) dual handwriting database. In: Proceedings of the Fifth International Conference on Document Analysis and Recognition, pp. 455-458, Bangalore, India (1999)
14. Zhang, G.P.: Neural networks for classification: a survey. IEEE Transactions on Systems, Man and Cybernetics, Part C: Applications and Reviews 30(4), 451-462 (2000)