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dc.contributor.authorErgun, Asli
dc.contributor.authorErgun, Serkan
dc.contributor.authorUnlu, Mehmet Zubeyir
dc.contributor.authorGungor, Cengiz
dc.description25th Signal Processing and Communications Applications Conference (SIU)en_US
dc.descriptionUnlu, Mehmet Z/0000-0003-1605-0160en_US
dc.description.abstractIn image registration process, it is necessary to find the similarity of the images and thetranslation, rotation and scaling transformation parameter values that maximize the similarity between the two images. When the similarity measure and related parameters are calculated, information theory based entropic graphs can be used. In this study, similarity and optimization measures are compared on different entropic graphs. It has been seen that skeleton branch feature points to build entropic graphs give successful results.en_US
dc.description.sponsorshipTurk Telekom, Arcelik A S, Aselsan, ARGENIT, HAVELSAN, NETAS, Adresgezgini, IEEE Turkey Sect, AVCR Informat Technologies, Cisco, i2i Syst, Integrated Syst & Syst Design, ENOVAS, FiGES Engn, MS Spektral, Istanbul Teknik Univen_US
dc.relation.ispartofseriesSignal Processing and Communications Applications Conference
dc.subjectEntropic graphsen_US
dc.subjectimage registrationen_US
dc.subjectparameter search optimization techniqueen_US
dc.subjectskeleton branch featuresen_US
dc.titleRegistration and Optimization in Fintropic Graphs Using Branch Skeleton Featuresen_US
dc.relation.journal2017 25Th Signal Processing And Communications Applications Conference (Siu)en_US
dc.contributor.departmentIzmir Isntitute of Technologyen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US

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