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dc.contributor.advisorDimakis, Alexandros G.
dc.creatorChucri, Samer Gergesen
dc.date.accessioned2013-12-18T16:23:31Zen
dc.date.issued2013-05en
dc.date.submittedMay 2013en
dc.identifier.urihttp://hdl.handle.net/2152/22742en
dc.descriptiontexten
dc.description.abstractThe problem of archiving photos is becoming increasingly important as image databases are growing more popular, and larger in size. One could take the example of any social networking website, where users share hundreds of photos, resulting in billions of total images to be stored. Ideally, one would like to use minimal storage to archive these images, by making use of the redundancy that they share, while not sacrificing quality. We suggest a compression algorithm that aims at compressing across images, rather than compressing images individually. This is a very novel approach that has never been adopted before. This report presents the design of a new image database compression tool. In addition to that, we implement a complete system on C++, and show the significant gains that we achieve in some cases, where we compress 90% of the initial data. One of the main tools we use is Locally Sensitive Hashing (LSH), a relatively new technique mainly used for similarity search in high-dimensions.en
dc.format.mimetypeapplication/pdfen
dc.language.isoen_USen
dc.subjectImage compressionen
dc.subjectLocally sensitive hashingen
dc.subjectCompression algorithmsen
dc.titleImage compression using locally sensitive hashingen
dc.date.updated2013-12-18T16:23:31Zen
dc.description.departmentElectrical and Computer Engineeringen
thesis.degree.departmentElectrical and Computer Engineeringen
thesis.degree.disciplineElectrical and Computer Engineeringen
thesis.degree.grantorThe University of Texas at Austinen
thesis.degree.levelMastersen
thesis.degree.nameMaster of Science in Engineeringen


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