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2017 | OriginalPaper | Chapter

5. Optical Character Recognition Systems for French Language

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

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

Publisher: Springer International Publishing

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Abstract

The optical character recognition (OCR) systems for French language were the most primitive ones and occupy a significant place in pattern recognition. The French language OCR systems have been used successfully in a wide array of commercial applications. The different challenges involved in the OCR systems for French language is investigated in this chapter. The pre-processing activities such as text region extraction, skew detection and correction, binarization, noise removal, character segmentation and thinning are 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 hierarchical fuzzy bidirectional recurrent neural networks (HFBRNN). The superiority of soft computing techniques is demonstrated through the experimental results.

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previous chapter Optical Character Recognition Systems for English Language
next chapter Optical Character Recognition Systems for German Language
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Metadata
Title
Optical Character Recognition Systems for French Language
Authors
Arindam Chaudhuri
Krupa Mandaviya
Pratixa Badelia
Soumya K. Ghosh
Copyright Year
2017
Book
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 Year: 2017

DOI
https://doi.org/10.1007/978-3-319-50252-6_5

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