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<p><b>Abstract</b>—In this work we present a self-organization matching approach to accomplish the recognition of handprinted characters drawn with thick strokes. This approach is used to flex the unknown handprinted character toward matching its object characters gradually. The extracted character features used in the self-organization matching are center loci, orientation, and major axes of ellipses which fit the inked area of the patterns. Simulations provide encouraging results using the proposed method.</p>
Handprinted character recognition, spatial topology distance, self-organizing map, neural networks, elastic matching.
Hsin-Chang Yang, Cheng-Yuan Liou, "Handprinted Character Recognition Based on Spatial Topology Distance Measurement", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 18, no. , pp. 941-945, September 1996, doi:10.1109/34.537349
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