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Simulation Tools and Techniques. 11th International Conference, SIMUtools 2019, Chengdu, China, July 8–10, 2019, Proceedings

Research Article

An Adaptive Threshold Algorithm for Offline Uyghur Handwritten Text Line Segmentation

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  • @INPROCEEDINGS{10.1007/978-3-030-32216-8_29,
        author={Eliyas Suleyman and Palidan Tuerxun and Kamil Moydin and Askar Hamdulla},
        title={An Adaptive Threshold Algorithm for Offline Uyghur Handwritten Text Line Segmentation},
        proceedings={Simulation Tools and Techniques. 11th International Conference, SIMUtools 2019, Chengdu, China, July 8--10, 2019, Proceedings},
        proceedings_a={SIMUTOOLS},
        year={2019},
        month={10},
        keywords={Text line segmentation Adaptive thresholding Offline Uyghur handwritten documents},
        doi={10.1007/978-3-030-32216-8_29}
    }
    
  • Eliyas Suleyman
    Palidan Tuerxun
    Kamil Moydin
    Askar Hamdulla
    Year: 2019
    An Adaptive Threshold Algorithm for Offline Uyghur Handwritten Text Line Segmentation
    SIMUTOOLS
    Springer
    DOI: 10.1007/978-3-030-32216-8_29
Eliyas Suleyman1, Palidan Tuerxun1, Kamil Moydin1, Askar Hamdulla1,*
  • 1: Xinjiang University
*Contact email: askar@xju.edu.cn

Abstract

This paper presents an effective text-line segmentation algorithm and evaluates its performance on Uyghur handwritten text document images. Projection based adaptive threshold selection mechanism is implemented to detect and segment the text lines with different valued thresholds. The robustness of the proposed algorithm is admirable that experiments on 210 Uyghur handwritten document image including 2570 text lines got correct segmentation by 97.70% precision and 99.01% recall rate and outperformed the compared classic text-line segmentation algorithm on same evaluation set.

Keywords
Text line segmentation Adaptive thresholding Offline Uyghur handwritten documents
Published
2019-10-24
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-030-32216-8_29
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