Model based table cell detection and content extraction from degraded document images
Proceeding of the workshop on Document Analysis and Recognition
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In this paper, we present a novel approach for detecting and removing pre-printed rule-lines from binary handwritten Arabic document images. The proposed technique is based on a directional local profiling approach for the detection of the rule-line locations. Then a refined adaptive vertical run-length search is designed for removing the rule-line pixels without much damaging to the text. They are also tolerate to the variations in the rule-lines such as broken lines, orientation changes and variation in the thickness of the rule-lines. Analysis of experimental results on the DARPA MADCAT Arabic handwritten document data indicates that the method is robust and is capable of correctly removing rule-lines.