Abstract
ABSTRACT This paper presents a novel approach for the multi-oriented text line extraction from historical handwrittenArabic documents. Because of the multi-orientation of lines and their dispersion in the page, we use an imagepaving algorithm that can progressively and locally determine the lines. The paving algorithm is initialized witha small window and then its size is corrected by extension until enough lines and connected components werefound. We use the Snake for line extraction. Once the paving is established, the orientation is determined usingthe Wigner-Ville distribution on the histogram projection prole. This local orientation is then enlarged to limitthe orientation in the neighborhood. Afterwards, the text lines are extracted locally in each zone basing onthe follow-up of the baselines and the proximity of connected components. Finally, the connected componentsthat overlap and touch in adjacent lines are separated. The morphology analysis of the terminal letters ofArabic words is here considered. The proposed approach has been experimented on 100 documents reaching anseparation accuracy of about 98.6%.Keywords: Handwritten Arabic documents, text line segmentation, skew angle estimation, Snake, Wigner-Villedistribution, overlapping and touching lines.
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