Integrated segmentation and recognition of connected Ottoman script

Yalniz, Ismet Zeki
Altıngövde, İsmail Sengör
Gudukbay, Ugur
Ulusoy, Ozgur
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. (C) 2009 Society of Photo-Optical Instrumentation Engineers. [DOI: 10.1117/1.3262346]


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Citation Formats
I. Z. Yalniz, İ. S. Altıngövde, U. Gudukbay, and O. Ulusoy, “Integrated segmentation and recognition of connected Ottoman script,” OPTICAL ENGINEERING, pp. 0–0, 2009, Accessed: 00, 2020. [Online]. Available: