• DocumentCode
    258973
  • Title

    Rule Line Detection and Removal in Handwritten Text Images

  • Author

    Imtiaz, Syed ; Nagabhushan, P. ; Gowda, Sahana D.

  • Author_Institution
    Dept. of Studies in Comput. Sci., Univ. of Mysore, Mysore, India
  • fYear
    2014
  • fDate
    8-10 Jan. 2014
  • Firstpage
    310
  • Lastpage
    315
  • Abstract
    Analysis of handwritten document images is one of the key areas of research in image processing domain. The objective of the analysis is to recognize the text components in an image and extract the intended information. However, inscription of handwriting usually would be on documents with rule lines, since they act as guide lines to the writer to ensure the writing remains straight and is of uniform size. These lines make the task of recognition difficult and hence removing them automatically becomes a major issue in text image processing. To accomplish this objective, an attempt is being made in this paper to remove the horizontal rule lines and vertical margin line for efficient recognition and analysis of the foreground text. Using mathematical morphology, predominant horizontal and vertical lines are removed leaving out stray lines which hinder the further processing of text. The stray lines are identified and removed using entropy with sliding window based on dynamic thresholding.
  • Keywords
    document image processing; entropy; handwriting recognition; image segmentation; mathematical morphology; text analysis; dynamic thresholding; entropy; handwritten document images; handwritten text images; mathematical morphology; rule line detection; rule line removal; text image processing; Educational institutions; Electronic mail; Entropy; Image restoration; Morphology; Noise; Text recognition; Entropy; Median filter; Morphology; Sliding window;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal and Image Processing (ICSIP), 2014 Fifth International Conference on
  • Conference_Location
    Jeju Island
  • Type

    conf

  • DOI
    10.1109/ICSIP.2014.55
  • Filename
    6754894