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In this article, we propose a novel scheme for online handwritten character recognition based on Levenshtein distance metric. Both shape and position information are considered in our feature representation scheme. The shape information is encoded by a string of quantized values of angular displacements between successive sample points along the trajectory of the handwritten character. The consecutive occurrences of same value in such a string are removed retaining only one of them. Next, each element in the resulting string is assigned an integral weight value proportional to the length of the segment of the trajectory represented by the corresponding element.

Added on September 6, 2017


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  • Contributed by : OHWR Consortium
  • Product Type : Research Paper
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  • Author : S. Dutta Chowdhury,U. Bhattacharya,S. K. Parui
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