Layout Analysis for Arabic Historical Document Images Using Machine Learning

Syed Saqib Bukhari, Thomas M. Breuel, Abedelkadir Asi, Jihad El-Sana
2012 2012 International Conference on Frontiers in Handwriting Recognition  
Page layout analysis is a fundamental step of any document image understanding system. We introduce an approach that segments text appearing in page margins (a.k.a side-notes text) from manuscripts with complex layout format. Simple and discriminative features are extracted in a connected-component level and subsequently robust feature vectors are generated. Multilayer perception classifier is exploited to classify connected components to the relevant class of text. A voting scheme is then
more » ... ed to refine the resulting segmentation and produce the final classification. In contrast to state-of-the-art segmentation approaches, this method is independent of block segmentation, as well as pixel level analysis. The proposed method has been trained and tested on a dataset that contains a variety of complex side-notes layout formats, achieving a segmentation accuracy of about 95%.
doi:10.1109/icfhr.2012.227 dblp:conf/icfhr/BukhariBAE12 fatcat:npw7po3mjrad7cg62bti736uzq