Gradient-based contour encoding for character recognition

Pattern Recognition

Volumn 29, Issue 7, 1996, Pages 1147-1160

  Srikantan, Geetha ^a,b   Lam, Stephen W ^a   Srihari, Sargur N ^a,b  

^a UNIVERSITY AT BUFFALO   (United States)

^b the State University of New York   (United States)

Author keywords

Classification; Contour encoding; Digit character recognition; Gradient; Stroke; Structure

Indexed keywords

ALGORITHMS; DATA STRUCTURES; FEATURE EXTRACTION; IMAGE CODING; NEURAL NETWORKS;

CONTOUR ENCODING; DIGIT CHARACTER RECOGNITION; GRADIENT REPRESENTATION; IMAGE PIXEL;

OPTICAL CHARACTER RECOGNITION;

EID: 0030193520     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/0031-3203(95)00146-8     Document Type: Article

References (19)

1. G. Nagy, Optical character recognition - theory and practice, in Handbook of Statistics - Classification, Pattern Recognition and Reduction of Dimensionality, Krishnaiah, P. R. and Kanal L. N. eds, pp. 621-649 (1982).
2. S. N. Srihari, High-performance reading machines, Proc. IEEE 80, 1120-1132 (1992).
3. S. N. Srihari and J. J. Hull, Character recognition, Encyclopaedia of Artificial Intelligence 1 (1992).
4. P. Palumbo, S. N. Srihari, J. Soh, R. Sridhar and V. Demjanenko, Postal address block location in real time, IEEE Comput. 34-42 (1992).
5. T. Hattori, T. Yamasaki, Y. Watanabe, H. Sanada and Y. Tezuka, Distance based vector fields method for feature extraction of characters and figures, in Proc. Systems, Man Cybern. Conf. pp. 207-212 (1991).
6. D.-S. Lee and S. N. Srihari, Handprinted digit recognition: a comparison of algorithms, in Pre-Proceedings, 3rd International Workshop on Frontiers in Handwriting Recognition, Partners' Press (1993).
7. Z. C. Li, C, Y. Suen and J. Guo, Computer algorithms for recognizing the distinct parts of handprinted characters, in Proc. Systems, Man Cybern. Conf. pp. 197-200. (1991).
8. H. Nishida and S. Mori, An algebraic approach to automatic construction of structural models, IEEE Trans. Pattern Anal. Mach. Intell. 15, 1298-1311 (1994).
9. J. S. Smith, M. O. Bourgoin, K. Sims and H. L. Voorhees, Handwritten character classification using nearest neighbor in large databases, IEEE Trans. Pattern Anal. Mach. Intell. 16, 915-919 (1994).
10. L. Wang and T. Pavlidis, Direct gray-scale extraction of features for character recognition, IEEE Trans. Pattern Anal. Mach. Intell. 15, 1053-1067 (1993).
11. M. Revow, C. K. I. Williams and G. E. Hinton, Using mixtures of deformable models to capture variations in hand-printed digits, in Pre-Proceedings, 3rd International Workshop on Frontiers in Handwriting Recognition, pp. 142-152. Partners' Press (1993).
12. J. Birk, R. Kelley, N. Chen and L. Wilson, Image feature extraction using diameter-limited gradient direction histograms, IEEE Trans. Pattern Anal. Mach. Intell, 1, 228-235 (1979).
13. D. H. Hubel, Eye, Brain and Vision Scientific American Library (1988).
14. G. Srikantan, Gradient representation for handwritten character recognition, in Pre-Proceedings, 3rd International Workshop on Frontiers in Handwriting Recognition. Partners' Press (1993).
15. G. Srikantan, S. W. Lam and S. N. Srihari, Gradient-based contour encoding for grayscale character recognition, in SPIE Conf. Character Recog. Technol SPIE Press (1993).
16. S. W. Lam, A. C. Girardin and S. N. Srihari, Gray-scale character recognition using boundary features, in SPIE Conf. Proc. Character Recog. Digitization Technol. pp. 98-105 (1992).
17. W. K. Pratt, Digital Image, Processing, John Wiley (1991).
18. R. O. Duda and P. E. Hart, Pattern Classification and Scene Analysis. John Wiley (1973).
19. D. E. Rumelhart et al., Parallel Distributed Processing: Foundations. The MIT Press (1986).