Vehicle Discrimination Using a Combined Multiple Features Based on Vehicle Face

In this paper, a new method for vehicle discrimination and recognition on the basis of combination of multiple features based vehicle face is proposed. The color difference, vehicle face pattern difference and logo matching degree are getting together to improve the performance of vehicle discrimination. This method is assessed on a set of 200 images that belong to five distinctive vehicle manufacturers. A series of experiments are conducted, splitting the 300 pairs of images to a training set and a test set, respectively. It is shown that the enhanced feature combination approach (CMN) proposed in this paper boosts the recogni- tion accuracy compared with the CM and CN method. The reported results indi- cate a high classification rate in similar or different vehicles and a fast processing time, making it suitable for real-time applications.

[1]  Takeo Kato,et al.  Preceding vehicle recognition based on learning from sample images , 2002, IEEE Trans. Intell. Transp. Syst..

[2]  Wei Wang,et al.  Real-time vehicle classification based on eigenface , 2011, 2011 International Conference on Consumer Electronics, Communications and Networks (CECNet).

[3]  Timothy F. Cootes,et al.  Analysis of Features for Rigid Structure Vehicle Type Recognition , 2004, BMVC.

[4]  Mohan M. Trivedi,et al.  A General Active-Learning Framework for On-Road Vehicle Recognition and Tracking , 2010, IEEE Transactions on Intelligent Transportation Systems.

[5]  Naixue Xiong,et al.  A Neural Network Based Vehicle Classification System for Pervasive Smart Road Security , 2009, J. Univers. Comput. Sci..

[6]  Tatsuya Yoshida,et al.  Vehicle Classification System with Local-Feature Based Algorithn Using CG Model Images , 2002 .

[7]  Bailing Zhang,et al.  Classification of Vehicle Make by Combined Features and Random Subspace Ensemble , 2011, 2011 Sixth International Conference on Image and Graphics.

[8]  Harpreet S. Sawhney,et al.  Shapeme histogram projection and matching for partial object recognition , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[9]  Eleftherios Kayafas,et al.  Vehicle Logo Recognition Using a SIFT-Based Enhanced Matching Scheme , 2010, IEEE Transactions on Intelligent Transportation Systems.

[10]  Liang Li,et al.  Vehicle color recognition using monocular camera , 2011, 2011 International Conference on Wireless Communications and Signal Processing (WCSP).

[11]  Henrik I. Christensen,et al.  Computational visual attention systems and their cognitive foundations: A survey , 2010, TAP.