ntegrated segmentation and recognition of onnected Ottoman script

smet Zeki Yalniz smail Sengor Altingovde ğur Güdükbay zgür Ulusoy ilkent University epartment of Computer Engineering ilkent, Ankara, 06800 urkey -mail: [email protected] Abstract. We propose a novel context-sensitive segmentation and recognition method for connected letters in Ottoman script. This method first extracts a set of segments from a connected script and determines the candidate letters to which extracted segments are most similar. Next, a function is defined for scoring each different syntactically correct sequence of these candidate letters. To find the candidate letter sequence that maximizes the score function, a directed acyclic graph is constructed. The letters are finally recognized by computing the longest path in this graph. Experiments using a collection of printed Ottoman documents reveal that the proposed method provides 90% precision and recall figures in terms of character recognition. In a further set of experiments, we also demonstrate that the framework can be used as a building block for an information retrieval system for digital Ottoman archives. © 2009 Society of Photo-Optical Instrumentation Engineers. DOI: 10.1117/1.3262346