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Segmentation of Isolated and Touching Characters in Offline Handwritten Gurmukhi Script Recognition
Author(s) -
Munish Kumar,
M. K. Jindal,
Richa Sharma
Publication year - 2014
Publication title -
international journal of information technology and computer science
Language(s) - English
Resource type - Journals
eISSN - 2074-9015
pISSN - 2074-9007
DOI - 10.5815/ijitcs.2014.02.08
Subject(s) - computer science , artificial intelligence , segmentation , speech recognition , pattern recognition (psychology) , natural language processing
Segmentation of a word into characters is one of the important challenges in optical character recognition. This is even more challenging when we segment characters in an offline handwritten document. Touching characters make this problem more complex. In this paper, we have applied water reservoir based technique for identification and segmentation of touching characters in handwritten Gurmukhi words. Touching characters are segmented based on reservoir base area points. We could achieve 93.51% accuracy for character segmentation with this method. If the characters are neither broken nor overlapping, then this technique shall produce even better results.

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