Text line segmentation in handwritten documents using Mumford-Shah model

  • Authors:
  • Xiaojun Du;Wumo Pan;Tien D. Bui

  • Affiliations:
  • Department of Computer Science and Software Engineering, Concordia University, Montreal, Quebec, Canada;Department of Computer Science and Software Engineering, Concordia University, Montreal, Quebec, Canada;Department of Computer Science and Software Engineering, Concordia University, Montreal, Quebec, Canada

  • Venue:
  • Pattern Recognition
  • Year:
  • 2009

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Abstract

Text line segmentation in handwritten documents is an important step in document image processing. We present a new text line segmentation method based on the Mumford-Shah model. The algorithm is script independent. In addition, we use morphing to remove overlaps between neighboring text lines and connect broken ones. Experimental results show the validity of our method.