Arabic Handwritten Text Line Extraction by Applying an Adaptive Mask to Morphological Dilation

  • Authors:

  • Muna Khayyat;Louisa Lam;Ching Y. Suen;Fei Yin;Cheng-Lin Liu

  • Affiliations:

  • -;-;-;-;-

  • Venue:
  • DAS '12 Proceedings of the 2012 10th IAPR International Workshop on Document Analysis Systems
  • Year:
  • 2012

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Abstract

This paper presents a robust method for handwritten text line extraction. We use morphological dilation with a dynamic adaptive mask for line extraction. Line separation occurs because of the repulsion and attraction between connected components. The characteristics of the Arabic script are considered to ensure a high performance of the algorithm. Our method is evaluated on the CENPARMI Arabic handwritten documents database which contains multi-skewed and touching lines. With a matching score of 0.95, our method achieved precision and recall rates of 96:3% and 96:7% respectively, which demonstrate the effectiveness of our approach.