Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/1996
Title: Automated Vehicle Classification with Image Processing and Computational Intelligence
Authors: Sarıkan, Selim S.
Özbayoğlu, Ahmet Murat
Zilci, Oğuzhan
142991
Keywords: Vehicle Classification
Computational Intelligence
Image Processing
Intelligent Transportation Systems
Issue Date: 2017
Publisher: ELSEVIER Science BV
Source: Sarikan, S. S., Ozbayoglu, A. M., & Zilci, O. (2017). Automated vehicle classification with image processing and computational intelligence. Procedia computer science, 114, 515-522.
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.
Description: Complex Adaptive Systems Conference on Engineering Cyber Physical Systems (CAS) (2017 : Chicago, IL)
URI: https://www.sciencedirect.com/science/article/pii/S1877050917318161?via%3Dihub
https://hdl.handle.net/20.500.11851/1996
ISSN: 1877-0509
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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