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Character recognition based on non-linear multi-projection profiles measure |
K C SANTOSH1,*( ),Laurent WENDLING2 |
1. US National Library of Medicine (NLM), National Institutes of Health (NIH), Bethesda MD 20894, USA 2. SIP-LIPADE, Université Paris Descartes (Paris V), Paris 75270 Cedex 06, France |
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Abstract In this paper, we study a method for isolated handwritten or hand-printed character recognition using dynamic programming for matching the non-linear multiprojection profiles that are produced from the Radon transform. The idea is to use dynamic time warping (DTW) algorithm to match corresponding pairs of the Radon features for all possible projections. By using DTW, we can avoid compressing feature matrix into a single vector which may miss information. It can handle character images in different shapes and sizes that are usually happened in natural handwriting in addition to difficulties such as multi-class similarities, deformations and possible defects. Besides, a comprehensive study is made by taking a major set of state-ofthe-art shape descriptors over several character and numeral datasets from different scripts such as Roman, Devanagari, Oriya, Bangla and Japanese-Katakana including symbol. For all scripts, the method shows a generic behaviour by providing optimal recognition rates but, with high computational cost.
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Keywords
character recognition
the Radon features
dynamic programming
shape descriptors
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Corresponding Author(s):
K C SANTOSH
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Just Accepted Date: 31 December 2014
Issue Date: 24 September 2015
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