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International Journal of Image, Graphics and Signal Processing(IJIGSP)

ISSN: 2074-9074 (Print), ISSN: 2074-9082 (Online)

Published By: MECS Press

IJIGSP Vol.5, No.4, Apr. 2013

Video Analytics Algorithm for Automatic Vehicle Classification (Intelligent Transport System)

Full Text (PDF, 675KB), PP.38-45


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Author(s)

ArtaIftikhar,Ali Javed

Index Terms

ITS, Masking, Ontology, ROI, Vehicle Detection, Vehicle classification

Abstract

Automated Vehicle detection and classification is an important component of intelligent transport system. Due to significant importance in various fields such as traffic accidents avoidance, toll collection, congestion avoidance, terrorist activities monitoring, security and surveillance systems, intelligent transport system has become important field of study. Various technologies have been used for detecting and classifying vehicles automatically. Automated vehicle detection is broadly divided into two types- Hardware based and software based detection. Various algorithms have been implemented to classify different vehicles from videos. In this paper an efficient and economical solution for automatic vehicle detection and classification is proposed. The proposed system first isolates the object through background subtraction followed by vehicle detection using ontology. Vehicle detection is based on low level features such as shape, size, and spatial location. Finally system classifies vehicles into one of the known classes of vehicle based on size.

Cite This Paper

ArtaIftikhar,Ali Javed,"Video Analytics Algorithm for Automatic Vehicle Classification (Intelligent Transport System)", IJIGSP, vol.5, no.4, pp.38-45, 2013.DOI: 10.5815/ijigsp.2013.04.05

Reference

[1]Wei Wang, Yulong Shang, Jinzhi Guo, Zhiwei Qian," Real-time vehicle classification based on eigenface" Consumer Electronics, Communications and Networks (CECNet), 2011 IEEE International Conference.

[2]Jun-Wei Hsieh," Automatic Traffic Surveillance System for Vehicle Tracking and Classification", june 2006 Intelligent Transportation Systems, IEEE Transactions, Journals & Magazines

[3]Goyal, A, "A Neural Network based Approach for the Vehicle Classification", Computational Intelligence in Image and Signal Processing, 2007. CIISP 2007. IEEE Symposium, 1-5 April 2007

[4]Tao Xu ,Hong Liu , YueliangQian , Han Zhang, "A novel method for people and vehicle classification based on Hough line feature", Information Science and Technology (ICIST), 2011 International Conference , 26-28 March 2011

[5]Xiaoxu Ma; Grimson, W.E.L. ," Edge-based rich representation for vehicle classification", Computer Vision, 2005. ICCV 2005. Tenth IEEE International Conference, 17-21 Oct. 2005

[6]Mazaheri, M. , "Real time adaptive background estimation and road segmentation for vehicle classification", Electrical Engineering (ICEE), 2011 19th Iranian Conference, 17-19 May 2011

[7]Jin-Cyuan Lai ;Shih-Shinh Huang ; Chien-Cheng Tseng , "Image-based vehicle tracking and classification on the highway", Green Circuits and Systems (ICGCS), 2010 International Conference, 21-23 June 2010

[8]Zezhi Chen ,Pears, N. ; Freeman, M. ; ," Road vehicle classification using Support Vector Machines", Intelligent Computing and Intelligent Systems, 2009. ICIS 2009. IEEE International Conference, 20-22 Nov. 2009

[9]Kafai, M. ; Bhanu, B. ," Dynamic Bayesian Networks for Vehicle Classification in Video", Industrial Informatics, IEEE Transactions , Journals & Magazines, Feb. 2012

[10]Zhong Qin, Guangzhou, "Method of vehicle classification based on video", Advanced Intelligent Mechatronics, 2008. IEEE/ASME International Conference, 2-5 July 2008

[11]PeijinJi; Lianwen Jin; Xutao Li," Vision-based Vehicle Type Classification Using Partial Gabor Filter Bank", Automation and Logistics, 2007 IEEE International Conference, 18-21 Aug. 2007

[12]Canny edge detection, http://en.wikipedia.org/wiki/Canny_edge_detector