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Drop flow method: an iterative algorithm for complete segmentation of Devanagari ancient manuscripts

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Abstract

One of the major challenges of ancient manuscripts recognition is character segmentation. Because of many distinct features of ancient documents (thick characters, overlapping and touching characters), character segmentation is a very difficult task. Devanagari ancient manuscripts consist of vowels, consonants, modifiers, conjuncts and compound characters. Using existing techniques, segmentation of overlapping and touching characters is problematic. In this paper, an iterative character segmentation algorithm is presented for ancient documents in Devanagari script. At the beginning, the lines are extracted from the ancient documents by dividing the document image into vertical stripes and then using piecewise horizontal projection profiles. After that, these lines are segmented into words using vertical projection profiles and finally, words are segmented in characters using an iterative algorithm. In each iteration, character segmentation is refined. In the present work, we have proposed a new algorithm with the name ‘Drop Flow Method’ to find the segmentation path between touching components. The proposed algorithm can segment touching characters and 96.0% accuracy has been achieved for complete segmentation of Devanagari ancient manuscripts.

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Authors and Affiliations

  1. Department of Computer Science, D.A.V. College, Abohar, Punjab, India

    Sonika Rani Narang

  2. Department of Computer Science & Applications, Panjab University Regional Centre, Muktsar, Punjab, India

    Manish Kumar Jindal

  3. Department of Computational Sciences, Maharaja Ranjit Singh Punjab Technical University, Bathinda, Punjab, India

    Munish Kumar

Authors
  1. Sonika Rani Narang
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  2. Manish Kumar Jindal
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  3. Munish Kumar
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Correspondence to Munish Kumar.

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Narang, S.R., Jindal, M.K. & Kumar, M. Drop flow method: an iterative algorithm for complete segmentation of Devanagari ancient manuscripts. Multimed Tools Appl 78, 23255–23280 (2019). https://doi.org/10.1007/s11042-019-7620-6

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  • DOI: https://doi.org/10.1007/s11042-019-7620-6

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