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dc.contributor.advisorŞahin, Pınar Duygulu
dc.contributor.authorAdıgüzel, Hande
dc.date.accessioned2016-01-08T18:26:19Z
dc.date.available2016-01-08T18:26:19Z
dc.date.issued2013
dc.identifier.urihttp://hdl.handle.net/11693/15892
dc.descriptionAnkara : The Department of Computer Engineering and the Graduate School of Engineering and Science of Bilkent University, 2013.en_US
dc.descriptionThesis (Master's) -- Bilkent University, 2013.en_US
dc.descriptionIncludes bibliographical references leaves 80-88.en_US
dc.description.abstractLarge archives of historical documents attract many researchers from all around the world. The increasing demand to access those archives makes automatic retrieval and recognition of historical documents crucial. Ottoman archives are one of the largest collections of historical documents. Although Ottoman is not a currently spoken language, many researchers from all around the world are interested in accessing the archived material. This thesis proposes two Ottoman document analysis studies; first one is a crucial pre-processing task for retrieval and recognition which is segmentation of documents. Second one is a more specific retrieval and recognition problem which aims matching Islamic patterns is Kufic images. For the first segmentation task, layout, line and word segmentation is studied. Layout segmentation is obtained via Log-Gabor filtering. Four different algorithms are proposed for line segmentation and finally a simple morphological method is preferred for word segmentation. Datasets are constructed with documents from both Ottoman and other languages (English, Greek and Bangla) to test the script-independency of the methods. Experiments show that our segmentation steps give satisfactory results. The second task aims to detect Islamic patterns in Kufic images. The sub-patterns are considered as basic units and matching is used for the analysis. Graphs are preferred to represent subpatterns where graph and sub-graph isomorphism are used for matching them. Kufic images are analyzed in three different ways. Given a query pattern, all the instances of the query can be found through retrieval. Going further, through known patterns images can be automatically labeled in the entire dataset. Finally, patterns that repeat inside an image can be automatically discovered. As there is no existing Kufic dataset, a new one is constructed by collecting images from the Internet and promising results are obtained on this dataset.en_US
dc.description.statementofresponsibilityAdıgüzel, Handeen_US
dc.format.extentxiv, 101, graphics, illustrations, facsimsen_US
dc.language.isoEnglishen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectHistorical Manuscriptsen_US
dc.subjectOttoman Documentsen_US
dc.subjectLayout Segmentationen_US
dc.subjectLine Segmentationen_US
dc.subjectWord Segmentationen_US
dc.subjectIslamic Pattern Matchingen_US
dc.subject.lccQA76.9.T48 A35 2013en_US
dc.subject.lcshText processing (Computer science)en_US
dc.subject.lcshInformation storage and retrieval systems.en_US
dc.subject.lcshArchives--Data processing.en_US
dc.subject.lcshWriting--Identification--Data processing.en_US
dc.subject.lcshComputational linguistics.en_US
dc.subject.lcshNatural language processing.en_US
dc.titleSegmentation based Ottoman text and matching based Kufic image analysisen_US
dc.typeThesisen_US
dc.departmentDepartment of Computer Engineeringen_US
dc.publisherBilkent Universityen_US
dc.description.degreeM.S.en_US
dc.identifier.itemidB139311


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