Wael Abd-Almageed

Handwritten Arabic Text Line Segmentation Using Affinity Propagation

TitleHandwritten Arabic Text Line Segmentation Using Affinity Propagation
Publication TypeConference Paper
Year of Publication2010
AuthorsJ. Kumar, W. Abd-Almageed, L. Kang, and D. Doermann
Conference NameProceedings of the 9th IAPR International Workshop on Document Analysis Systems
Conference LocationNew York, NY, USA
Abstract

In this paper, we present a novel graph-based method for extracting handwritten text lines in monochromatic Arabic document images. Our approach consists of two steps - Coarse text line estimation using primary components which define the line and assignment of diacritic components which are more difficult to associate with a given line. We first estimate local orientation at each primary component to build a sparse similarity graph. We then, use a shortest path algorithm to compute similarities between non-neighboring components. From this graph, we obtain coarse text lines using two estimates obtained from Affinity propagation and Breadth-first search. In the second step, we assign secondary components to each text line. The proposed method is very fast and robust to non-uniform skew and character size variations, normally present in handwritten text lines. We evaluate our method using a pixel-matching criteria, and report 96% accuracy on a dataset of 125 Arabic document images. We also present a proximity analysis on datasets generated by artificially decreasing the spacings between text lines to demonstrate the robustness of our approach.

URLhttp://doi.acm.org/10.1145/1815330.1815348
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