Text Line Segmentation in Handwritten Document Images Using Tensor Voting

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著者

    • NGUYEN Toan Dinh
    • Department of Electronics and Computer Engineering, Chonnam National University
    • LEE Gueesang
    • Department of Electronics and Computer Engineering, Chonnam National University

抄録

A novel grouping approach to segment text lines from handwritten documents is presented. In this text line segmentation algorithm, for each text line, a text string that connects the center points of the characters in this text line is built. The text lines are then segmented using the resulting text strings. Since the characters of the same text line are situated close together and aligned on a smooth curve, 2D tensor voting is used to reduce the conflicts when building these text strings. First, the text lines are represented by separate connected components. The center points of these connected components are then encoded by second order tensors. Finally, a voting process is applied to extract the curve saliency values and normal vectors, which are used to remove outliers and build the text strings. The experimental results obtained from the test dataset of the ICDAR 2009 Handwriting Segmentation Contest show that the proposed method generates high detection rate and recognition accuracy.

収録刊行物

  • IEICE transactions on fundamentals of electronics, communications and computer sciences

    IEICE transactions on fundamentals of electronics, communications and computer sciences 94(11), 2434-2441, 2011-11-01

    The Institute of Electronics, Information and Communication Engineers

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各種コード

  • NII論文ID(NAID)
    10030192239
  • NII書誌ID(NCID)
    AA10826239
  • 本文言語コード
    ENG
  • 資料種別
    ART
  • ISSN
    09168508
  • データ提供元
    CJP書誌  J-STAGE 
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