Title: Off-line Handwritten Arabic Words Segmentation Based on Structural Features and Connected Components Analysis
Authors: Elzobi, Moftah
Al-Hamadi, Ayoub
Al Aghbari, Zaher
Citation: WSCG '2011: Communication Papers Proceedings: The 19th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, p. 135-142.
Issue Date: 2011
Publisher: Václav Skala - UNION Agency
Document type: konferenční příspěvek
URI: http://wscg.zcu.cz/WSCG2011/!_2011_WSCG-Short_Papers.pdf
ISBN: 978-80-86943-82-4
Keywords: arabské ruční písmo;segmentace obrazu;rozpoznávání vzorů;topologické znaky
Keywords in different language: arabic handwriting;image segmentation;pattern recognition;topological features
Abstract: A precise and efficient segmentation for handwritten Arabic text is a vital prerequisite for the accuracy of the subsequent recognition phase. In this paper, we present a dualphase segmentation approach. The proposed approach starts first by detecting and resolving sub-words overlapping, then a topological features based segmentation is applied by means of a set of heuristic rules. Because of its crucial importance, the segmentation phase is preceded by a handwritten specific preprocessing phase, that considers issues like word’s skew- and slant- correction. The proposed approach has been successfully tested on a database of handwritten Arabic words, that contains more than 3000 words images. The results were very promising and indicating the efficiency of our approach.
Rights: © Václav Skala - UNION Agency
Appears in Collections:WSCG '2011: Communication Papers Proceedings

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