Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/3854
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dc.contributor.authorErkut, Umur-
dc.contributor.authorBostancıoğlu, F.-
dc.contributor.authorErten, M.-
dc.contributor.authorÖzbayoğlu, Ahmet Murat-
dc.contributor.authorSolak, E.-
dc.date.accessioned2020-10-22T16:40:35Z-
dc.date.available2020-10-22T16:40:35Z-
dc.date.issued2019-11
dc.identifier.citationErkut, U., Bostancıoğlu, F., Erten, M., Özbayoğlu, A. M. and Solak, E. (2019, November). HSV color histogram based image retrieval with background elimination. In 2019 1st International Informatics and Software Engineering Conference (UBMYK) (pp. 1-5). IEEE.en_US
dc.identifier.urihttps://hdl.handle.net/20.500.11851/3854-
dc.identifier.urihttps://ieeexplore.ieee.org/document/8965513-
dc.description.abstractIn this study, a new content based image retrieval (CBIR) method, which uses HSV histogram data is proposed. The model uses the HSV histogram to find the background from the image by analyzing the peaks in the histogram data and performing a moving window algorithm to identify the region within the histogram that belongs to the background colors. After identifying the background information, the sections of the image that are part of the background are removed from the original image and the remaining foreground or content information is stored for comparison with other images. In order to verify the methodology, a graphical user interface is developed and 1000 different images from 10 different groups from the coral database are put into the image database for comparison. The analysis and preliminary tests show that comparing only the foreground information of the images pro-vided better results than comparing images themselves, especially when searching for particular objects within the images. This algorithm can also be used as a background elimination technique to reduce the storage requirements of images and the comparison time between images can be reduced significantly. © 2019 IEEE.en_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof1st International Informatics and Software Engineering Conference: Innovative Technologies for Digital Transformation, IISEC 2019 - Proceedingsen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectBackground correctionen_US
dc.subjectbackground eliminationen_US
dc.subjectCBIRen_US
dc.subjectContent based image retrievalen_US
dc.subjecthistogram enhancementen_US
dc.subjectHSV histogramen_US
dc.subjectobject retrievalen_US
dc.subjectRGB histogramen_US
dc.titleHsv Color Histogram Based Image Retrieval With Background Eliminationen_US
dc.typeConference Objecten_US
dc.departmentFaculties, Faculty of Engineering, Department of Computer Engineeringen_US
dc.departmentFakülteler, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümütr_TR
dc.authorid0000-0001-7998-5735-
dc.identifier.scopus2-s2.0-85079225778en_US
dc.institutionauthorÖzbayoğlu, Ahmet Murat-
dc.identifier.doi10.1109/UBMYK48245.2019.8965513-
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
item.openairetypeConference Object-
item.languageiso639-1en-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
crisitem.author.dept02.1. Department of Artificial Intelligence Engineering-
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
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