Yalniz, I. Z.Altingovde, I. S.Güdükbay, UğurUlusoy, Özgür2016-02-082016-02-082009-110091-3286http://hdl.handle.net/11693/22533We 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.EnglishConnected scriptsHistorical document analysisInformation retrievalOptical character recognitionBuilding blockesContext-sensitiveDirected acyclic graphsIntegrated segmentation and recognitionLongest pathPrecision and recallRecognition methodsScore functionExperimentsSearch enginesArticle10.1117/1.3262346