Abstract
The problem of Optical Character Recognition (OCR) can be solved by set operators implemented as programs for a Morphological Machine (MMach). In this paper, we present two techniques to boost such programs: (1) Anchoring and (2) Edge Noise Filtering by Stamp. The power of these techniques is demonstrated by some impressive experimental results.
The authors have received partial support from FAPESP and CNPq. The authors also thanks the students Teofilo E. Campos, Rogerio Feris, Archias A. de A. Filho, Franklin C. Flores and Fabiano C. Sousa, that have developed part of the software used in this paper.
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© 2002 Kluwer Academic/Plenum Publishers
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Barrera, J., Brun, M., Terada, R., Dougherty, E.R. (2002). Boosting OCR Classifier by Optimal Edge Noise Filtering. In: Goutsias, J., Vincent, L., Bloomberg, D.S. (eds) Mathematical Morphology and its Applications to Image and Signal Processing. Computational Imaging and Vision, vol 18. Springer, Boston, MA. https://doi.org/10.1007/0-306-47025-X_40
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DOI: https://doi.org/10.1007/0-306-47025-X_40
Publisher Name: Springer, Boston, MA
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