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Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 352))

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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Correspondence to Arindam Chaudhuri .

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Chaudhuri, A., Mandaviya, K., Badelia, P., Ghosh, S.K. (2017). Optical Character Recognition Systems for French Language. In: Optical Character Recognition Systems for Different Languages with Soft Computing. Studies in Fuzziness and Soft Computing, vol 352. Springer, Cham. https://doi.org/10.1007/978-3-319-50252-6_5

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

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-50251-9

  • Online ISBN: 978-3-319-50252-6

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