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Segmentation of Merged Lines and Script Identification in Handwritten Bilingual Documents

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Published:08 December 2017Publication History

ABSTRACT

Text line segmentation is a challenging task in Optical Character Recognition, due to writing style of writers and touching characters or Matra between lines. In this paper, we have proposed an algorithm for dividing the merged lines into individual multiple lines from Handwritten Bilingual (Marathi-English) documents. The algorithm is tested on different images; we have obtained promising results. Afterward, script is identifying at word level using fusion of moment based features and visual discriminating features. Two different classifiers are evaluated on a dataset consisting of 242 Marathi-English words for training and 82 words for testing. We have received average identification accuracy of 67% in K-NN classifier and 80.14% in SVM classifier.

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  • Published in

    cover image ACM Other conferences
    FIRE '17: Proceedings of the 9th Annual Meeting of the Forum for Information Retrieval Evaluation
    December 2017
    38 pages
    ISBN:9781450363822
    DOI:10.1145/3158354

    Copyright © 2017 ACM

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    • Published: 8 December 2017

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    • short-paper
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    Acceptance Rates

    Overall Acceptance Rate19of64submissions,30%

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