30 March 1995 Word recognition using a lexicon constrained by first/last character decisions
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Abstract
In lexicon based recognition of machine-printed word images, the size of the lexicon can be quite extensive. The recognition performance is closely related to the size of the lexicon. Recognition performance drops quickly when lexicon size increases. Here, we present an algorithm to improve the word recognition performance by reducing the size of the given lexicon. The algorithm utilizes the information provided by the first and last characters of a word to reduce the size of the given lexicon. Given a word image and a lexicon that contains the word in the image, the first and last characters are segmented and then recognized by a character classifier. The possible candidates based on the results given by the classifier are selected, which give us the sub-lexicon. Then a word shape analysis algorithm is applied to produce the final ranking of the given lexicon. The algorithm was tested on a set of machine- printed gray-scale word images which includes a wide range of print types and qualities.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sheila X. Zhao, Sheila X. Zhao, Sargur N. Srihari, Sargur N. Srihari, } "Word recognition using a lexicon constrained by first/last character decisions", Proc. SPIE 2422, Document Recognition II, (30 March 1995); doi: 10.1117/12.205812; https://doi.org/10.1117/12.205812
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