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Off-line constrained vocabulary cursive script recognition using visible features

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2 Author(s)
B. Ho ; Sch. of Comput. Eng., Nanyang Technol. Univ., Singapore, Singapore ; G. Leedham

This paper presents a model for off-line cursive script recognition. The method proposed combines both analytical and holistic approaches to solve the problem of cursive script recognition. The emphasis is to create a fast and reliable model for recognition. The holistic approach of extracting feature is used with the analytical approach of segmenting and recognizing the first character. Pre-processing, feature extraction, classifier, and phrase recognition are explained and used in this system. Results from a test set of 1294 images are presented based on three different word recognition methods that are experimented. This system is being used as a system to sort mails that are directed overseas, however, it can also be used for other requirements like word spotting in unconstrained text.

Published in:

Intelligent Information Systems Conference, The Seventh Australian and New Zealand 2001

Date of Conference:

18-21 Nov. 2001