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 conferenceObject |
URI: | http://wscg.zcu.cz/WSCG2011/!_2011_WSCG-Short_Papers.pdf http://hdl.handle.net/11025/10841 |
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 |
Files in This Item:
File | Description | Size | Format | |
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Elzobi.pdf | Plný text | 634,46 kB | Adobe PDF | View/Open |
Please use this identifier to cite or link to this item:
http://hdl.handle.net/11025/10841
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