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Dual classifier system for handprinted alphanumeric character recognition

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Abstract

This paper presents a dual classifier handprinted character recognition system that is implemented using Radial Basis Function (RBF) networks. Each classifier in the system extracts a different set of features from the input character and makes its own indpendent classification decision. The features used are the diagonal and partitioned radial projections, and the four-directional edge maps of the mage. The system then combines these decisions before giving a final classification output. Several different methods of desinging the combiner are examined. The proposed system is tested on a database of handprinted alphanumeric characters, and the results are fourd to be very promising.

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Authors and Affiliations

  1. Department of Electrical Engineering, National University of Singapore, 10 Kent Ridge Crescent, 119260, Singapore, Singapore

    Y. -C. Chim & A. A. Kassim

  2. Department of Industrial & Systems Engineering, National University of Singapore, Singapore

    Y. Ibrahim

Authors
  1. Y. -C. Chim
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  2. A. A. Kassim
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  3. Y. Ibrahim
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Correspondence to A. A. Kassim.

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Chim, Y.C., Kassim, A.A. & Ibrahim, Y. Dual classifier system for handprinted alphanumeric character recognition. Pattern Analysis & Applic 1, 155–162 (1998). https://doi.org/10.1007/BF01259365

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  • DOI: https://doi.org/10.1007/BF01259365

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