Yalnız, İsmet Zeki2016-01-082016-01-082008http://hdl.handle.net/11693/14738Ankara : The Department of Computer Engineering and the Institute of Engineering and Science of Bilkent University, 2008.Thesis (Master's) -- Bilkent University, 2008.Includes bibliographical references leaves 43-45.In this thesis, a novel context-sensitive segmentation and recognition method for connected letters in Ottoman script is proposed. This method first extracts a set of possible 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 very high 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.xii, 52 leavesEnglishinfo:eu-repo/semantics/openAccessOptical character recognition (OCR)Segmentation and recognition of connected scriptsConnected scriptsInformation retrieval (IR)TA1640 .Y34 2008Optical character recognition devices.Writing--Identification--Data processing.ThesisBILKUTUPB109234