Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.11851/1996
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Sarıkan, Selim S. | - |
dc.contributor.author | Özbayoğlu, Ahmet Murat | - |
dc.contributor.author | Zilci, Oğuzhan | - |
dc.date.accessioned | 2019-07-10T14:42:44Z | |
dc.date.available | 2019-07-10T14:42:44Z | |
dc.date.issued | 2017 | |
dc.identifier.citation | Sarikan, S. S., Ozbayoglu, A. M., & Zilci, O. (2017). Automated vehicle classification with image processing and computational intelligence. Procedia computer science, 114, 515-522. | en_US |
dc.identifier.issn | 1877-0509 | |
dc.identifier.uri | https://www.sciencedirect.com/science/article/pii/S1877050917318161?via%3Dihub | - |
dc.identifier.uri | https://hdl.handle.net/20.500.11851/1996 | - |
dc.description | Complex Adaptive Systems Conference on Engineering Cyber Physical Systems (CAS) (2017 : Chicago, IL) | |
dc.description.abstract | Classification of vehicles is an important part of an Intelligent Transportation System. In this study, image processing and machine learning techniques are used to classify vehicles in dedicated lanes. Images containing side view profile of vehicles are constructed using a commercially available light curtain. This capability makes the results robust to the variations in operational and environmental conditions. Time warping is applied to compensate for speed variations in traffic. Features such as windows and hollow areas are extracted to discriminate motorcycles against automobiles. The circularity and skeleton complexity values are used as features for the classifier. K-nearest neighbor and decision tree are chosen as the classifier models. The proposed method is evaluated on a public highway and promising classification results are achieved. (c) 2017 The Authors. Published by Elsevier B.V. | en_US |
dc.language.iso | en | en_US |
dc.publisher | ELSEVIER Science BV | en_US |
dc.relation.ispartof | Procedia Computer Science | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.subject | Vehicle Classification | en_US |
dc.subject | Computational Intelligence | en_US |
dc.subject | Image Processing | en_US |
dc.subject | Intelligent Transportation Systems | en_US |
dc.title | Automated Vehicle Classification With Image Processing and Computational Intelligence | en_US |
dc.type | Conference Object | en_US |
dc.department | Faculties, Faculty of Engineering, Department of Computer Engineering | en_US |
dc.department | Fakülteler, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü | tr_TR |
dc.identifier.volume | 114 | |
dc.identifier.startpage | 515 | |
dc.identifier.endpage | 522 | |
dc.authorid | 0000-0001-7998-5735 | - |
dc.identifier.wos | WOS:000419234000062 | en_US |
dc.identifier.scopus | 2-s2.0-85040024387 | en_US |
dc.institutionauthor | Özbayoğlu, Ahmet Murat | - |
dc.identifier.doi | 10.1016/j.procs.2017.09.022 | - |
dc.authorwosid | H-2328-2011 | - |
dc.authorscopusid | 6505999525 | - |
dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
dc.identifier.scopusquality | - | - |
item.openairetype | Conference Object | - |
item.languageiso639-1 | en | - |
item.grantfulltext | open | - |
item.fulltext | With Fulltext | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.cerifentitytype | Publications | - |
crisitem.author.dept | 02.1. Department of Artificial Intelligence Engineering | - |
Appears in Collections: | Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
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File | Description | Size | Format | |
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ozbayoglu_Automated.pdf | 563.93 kB | Adobe PDF | View/Open |
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