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Erschienen in:
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2017 | OriginalPaper | Buchkapitel

8. Optical Character Recognition Systems for Hindi Language

verfasst von : Arindam Chaudhuri, Krupa Mandaviya, Pratixa Badelia, Soumya K. Ghosh

Erschienen in: Optical Character Recognition Systems for Different Languages with Soft Computing

Verlag: Springer International Publishing

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Abstract

The optical character recognition (OCR) systems for Hindi language were the most primitive ones and occupy a significant place in pattern recognition. The Hindi language OCR systems have been used successfully in a wide array of commercial applications. The different challenges involved in the OCR systems for Hindi language is investigated in this Chapter. The pre-processing activities such as binarization, noise removal, skew detection, character segmentation and thinning performed on the datasets considered. The feature extraction is performed through fuzzy Hough transform. The feature based classification is performed through important soft computing techniques viz rough fuzzy multilayer perceptron (RFMLP), fuzzy support vector machine (FSVM), fuzzy rough support vector machine (FRSVM) and fuzzy markov random fields (FMRF). The superiority of soft computing techniques is demonstrated through the experimental results.

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Vorheriges Kapitel Optical Character Recognition Systems for Latin Language
Nächstes Kapitel Optical Character Recognition Systems for Gujrati Language
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Metadaten
Titel
Optical Character Recognition Systems for Hindi Language
verfasst von
Arindam Chaudhuri
Krupa Mandaviya
Pratixa Badelia
Soumya K. Ghosh
Copyright-Jahr
2017
Buch
Optical Character Recognition Systems for Different Languages with Soft Computing

Print ISBN: 978-3-319-50251-9

Electronic ISBN: 978-3-319-50252-6

Copyright-Jahr: 2017

DOI
https://doi.org/10.1007/978-3-319-50252-6_8