@inproceedings{d718a6e5892f4220a8fddae92b53299a,
title = "Removing rule-lines from binary handwritten Arabic document images using directional local profile",
abstract = "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.",
author = "Zhixin Shi and Srirangaraj Setlur and Venu Govindaraju",
year = "2010",
doi = "10.1109/ICPR.2010.472",
language = "English",
isbn = "9780769541099",
series = "Proceedings - International Conference on Pattern Recognition",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1916--1919",
booktitle = "Proceedings - 2010 20th International Conference on Pattern Recognition, ICPR 2010",
address = "United States",
}