Abstract
Machine simulation of human reading has been a subject of intensive research for almost four decades. Automatic Urdu character recognition remains a challenging task due to its cursive nature despite the fact that the latest improvements in recognition methods and systems for Latin script are very promising. This work introduces a robust approach based on statistical models that provide solution for recognition of Urdu text Nasta'liq style. Contrary to classical approaches which segment text into words, ligatures or characters, we intend to employ an implicit segmentation where text lines are recognized during segmentation. The developed system will be evaluated on standard Urdu text databases and compared with the state-of-the-art recognition techniques proposed till date.