Shape Code Based Lexicon Reduction for Offline Handwritten Word Recognition

Nara(2008)

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摘要
A novel method to reduce the lexicon size in handwritten word recognition is proposed in this paper. Due to large lexica, the computational cost of current word recognisers is often too high for practical applications. The proposed lexicon reduction method is based on character shape codes. We examine four different shape code mappings based on machine printed character font, on handprint, and on cursive handwriting. Experimental evaluation shows that the proposed method can reduce the computational effort while keeping the recognition rate high.
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关键词
cascade adaboost classifier,robust system,text localization,shape code,lexicon reduction,natural scene image,text detection,region-based method,localize text,offline handwritten word recognition,multiple feature,image recognition,writing,feature extraction,hidden markov models,handwriting recognition,hidden markov model,shape
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