Laser & Optoelectronics Progress, Volume. 58, Issue 14, 1410006(2021)

Layout Segmentation and Description of Tibetan Document Images Based on Adaptive Run Length Smoothing Algorithm

Yuanyuan Chen1, Weilan Wang2、*, Huaming Liu3, Zhengqi Cai1, and Penghai Zhao2
Author Affiliations
  • 1College of Mathematics and Computer Science, Northwest Minzu University, Lanzhou, Gansu 730030, China
  • 2Key Laboratory of China’s Ethnic Languages and Information Technology of Ministry of Education, Northwest Minzu University, Lanzhou, Gansu 730030, China
  • 3College of Computer and Information Engineering, Fuyang Normal University, Fuyang, Anhui 236041, China
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    References(16)

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    [12] Duan L J, Zhang X Q, Ma L L et al. Text extraction method for historical Tibetan document images based on block projections[J]. Optoelectronics Letters, 13, 457-461(2017).

    [13] Rais M, Goussies N A, Mejail M. Using adaptive run length smoothing algorithm for accurate text localization in images[M]. //Martin C S, Kim S W. Progress in pattern recognition, image analysis, computer vision, and applications. Lecture notes in computer science, 7042, 149-156(2011).

    [14] Papamarkos N, Tzortzakis J, Gatos B. Determination of run-length smoothing values for document segmentation[C]. //Proceedings of Third International Conference on Electronics, Circuits, and Systems, October 16, 1996, Rhodes, Greece., 684-687(1996).

    [15] Zhang L, Zhu Y, Wu G W. English document segmentation based on run-length smearing algorithm[J]. Acta Electronica Sinica, 27, 102-104(1999).

    [16] Chen Y. Design and implementation of printed Tibetan recognition software on android platform[D](2020).

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    Yuanyuan Chen, Weilan Wang, Huaming Liu, Zhengqi Cai, Penghai Zhao. Layout Segmentation and Description of Tibetan Document Images Based on Adaptive Run Length Smoothing Algorithm[J]. Laser & Optoelectronics Progress, 2021, 58(14): 1410006

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    Paper Information

    Category: Image Processing

    Received: Sep. 21, 2020

    Accepted: Nov. 12, 2020

    Published Online: Jul. 14, 2021

    The Author Email: Weilan Wang (wangweilan@xbmu.edu.cn)

    DOI:10.3788/LOP202158.1410006

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