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A hybrid group search optimization: firefly algorithm-based big data framework for ancient script recognition

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Abstract

Optical character recognition is becoming one of the widely researched areas in recent times. This research paper presents an optimization framework for ancient script recognition using the process of script or character segmentation. The proposed algorithm is based on evolutionary algorithm and capable of handing a continuous script of high-resolution data using concepts of big data. A hybrid combination of group search and firefly algorithm has been proposed in this research work and compared against recent works. Optimal classifications results are observed and recorded in this research paper.

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Funding

This work is not funded by any national/international bodies.

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Authors and Affiliations

  1. Faculty of Science and Humanities (Computer Sciences), Sathyabama University, Chennai, India

    T. S. Suganya

  2. Computer Science and Engineering, Panimalar Engineering College, Chennai, India

    S. Murugavalli

Authors
  1. T. S. Suganya
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  2. S. Murugavalli
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Correspondence to T. S. Suganya.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. This article does not contain any studies with animals performed by any of the authors.

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Communicated by V. Loia.

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Suganya, T.S., Murugavalli, S. A hybrid group search optimization: firefly algorithm-based big data framework for ancient script recognition. Soft Comput 24, 10933–10941 (2020). https://doi.org/10.1007/s00500-019-04596-x

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  • DOI: https://doi.org/10.1007/s00500-019-04596-x

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