Comparative Analysis of Vehicle Make and Model Recognition Techniques

Full Text (PDF, 430KB), PP.60-67

Views: 0 Downloads: 0


Faiza Ayub Syed 1,* Malik UsmanDilawar 2 Engr Ali Javed 1

1. Department of Software Engineering, University of Engineering & Technology, Taxila, Pakistan

2. Department of Computer Engineering, Center for Advance Studies in Engineering, Islamabad, Pakistan

* Corresponding author.


Received: 7 Nov. 2013 / Revised: 20 Dec. 2013 / Accepted: 6 Feb. 2014 / Published: 8 Mar. 2014

Index Terms

Make, Model Recognition (MMR), Vehicle Make, Model Recognition (VMMR)


Vehicle Make and Model Recognition (VMMR) has emerged as a significant element of vision based systems because of its application in access control systems, traffic control and monitoring systems, security systems and surveillance systems, etc. So far a number of techniques have been developed for vehicle recognition. Each technique follows different methodology and classification approaches. The evaluation results highlight the recognition technique with highest accuracy level. In this paper we have pointed out the working of various vehicle make and model recognition techniques and compare these techniques on the basis of methodology, principles, classification approach, classifier and level of recognition After comparing these factors we concluded that Locally Normalized Harris Corner Strengths (LHNS) performs best as compared to other techniques. LHNS uses Bayes and K-NN classification approaches for vehicle classification. It extracts information from frontal view of vehicles for vehicle make and model recognition.

Cite This Paper

Faiza Ayub Syed, Malik Usman Dilawar, Ali Javed,"Comparative Analysis of Vehicle Make and Model Recognition Techniques", IJIGSP, vol.6, no.4, pp. 60-67, 2014. DOI: 10.5815/ijigsp.2014.04.08


[1]Hongchao Zhang, Xuezhong Xiao, Qian Zhao, "Vehicle Make and Model Recognition with Unfixed Views", in proceedings of Chinese Conference on Pattern Recognition (CCPR), IEEE, 2010.

[2]David Anthony Torres, "More Local Structure Information for Make-Model Recognition", 2005.

[3]I.Zafar, E.A.Edirisinghe, B.S.Acar, "Localised Contourlet Features in Vehicle Make and Model Recognition", SPIE-IS&T, 2009.

[4]Kanwal Yousaf, Arta Iftikhar, Ali Javed, "Comparative Analysis of Automatic Vehicle Classification Techniques: A Survey", IJIGSP, 2012.

[5]Michal Conos, "Recognition of vehicle make from a frontal view", 2007.

[6]Apostolos P. Psyllos, Christos-Nikolaos E. Anagnostopoulos, Eleftherios Kayafas, "Vehicle Logo Recognition Using a SIFT-Based Enhanced Matching Scheme", IEEE, June 2010.

[7]Greg Pearce, Nick Pears, "Automatic Make and Model Recognition from Frontal Images of Cars", IEEE, 2011.

[8]M.Saquib Sarfraz, Ahmed Saeed, M.Haris Khan, Zahid Riaz, "Bayesian Prior Models for Vehicle Make and Model Recognition", ACM, 2009.

[9]V.S.Petrovic, T.F.Cootes "Vehicle Type Recognition with Match Refinement", " in proceedings of Seventeenth International Conference on Pattern Recognition (ICPR), IEEE, 2004.

[10]Remigiusz Baran, Andrzej Glowacz, Andrzej Matiolanski, "The efficient real-and non-real-time make and model recognition of cars", Springerlink, June 2013.

[11]Meena AbdelMaseeh, Islam Badreldin, Mohamed F. Abdelkader and Motaz El Saban, "Car Make and Model recognition combining global and local cues", in proceedings of Twentyfirst International Conference on Pattern Recognition (ICPR), IEEE, 2012.

[12]A. Psyllos, C.N. Anagnostopoulos, E. Kayafas, "Vehicle model recognition from frontal view image measurements", ScienceDirect, 2011.

[13]Gongde Guo, Hui Wang, David Bell, Yaxin Bi, Kieran Greer , "KNN Model-Based Approach in Classification", Springerlink, 2003.