A new scheme for unconstrained handwritten text-line segmentation

  • Authors:

  • Alireza Alaei;Umapada Pal;P. Nagabhushan

  • Affiliations:

  • Department of Studies in Computer Science, University of Mysore, Mysore 570 006, India;Computer Vision and Pattern Recognition Unit, Indian Statistical Institute, Kolkata 700108, India;Department of Studies in Computer Science, University of Mysore, Mysore 570 006, India

  • Venue:
  • Pattern Recognition
  • Year:
  • 2011

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Abstract

Variations in inter-line gaps and skewed or curled text-lines are some of the challenging issues in segmentation of handwritten text-lines. Moreover, overlapping and touching text-lines that frequently appear in unconstrained handwritten text documents significantly increase segmentation complexities. In this paper, we propose a novel approach for unconstrained handwritten text-line segmentation. A new painting technique is employed to smear the foreground portion of the document image. The painting technique enhances the separability between the foreground and background portions enabling easy detection of text-lines. A dilation operation is employed on the foreground portion of the painted image to obtain a single component for each text-line. Thinning of the background portion of the dilated image and subsequently some trimming operations are performed to obtain a number of separating lines, called candidate line separators. By using the starting and ending points of the candidate line separators and analyzing the distances among them, related candidate line separators are connected to obtain segmented text-lines. Furthermore, the problems of overlapping and touching components are addressed using some novel techniques. We tested the proposed scheme on text-pages of English, French, German, Greek, Persian, Oriya and Bangla and remarkable results were obtained.