Vehicle classification and counting system

Vehicle classification and counting play an important role in the intelligent transportation system, as they may serve to improve traffic congestion and safety problems. Therefore, this study has developed a real-time and vision-based vehicle classification and counting system. This will involve establishing Time-Spatial Images (TSI) from input video, removing the shadow portions in TSI through the use of Support Vector Machine (SVM) and Deterministic Non-Model Based Approach, detecting the Region of Interest (ROI) through a simple morphology process, and finally using the ROI accumulative curve method and Fuzzy Constraints Satisfaction Propagation (FCSP) to process occlusion problems and perform vehicle classification and counting. The experimental results have shown that the proposed method is feasible.

[1]  Mohan M. Trivedi,et al.  Shadow detection algorithms for traffic flow analysis: a comparative study , 2001, ITSC 2001. 2001 IEEE Intelligent Transportation Systems. Proceedings (Cat. No.01TH8585).

[2]  Bo Li,et al.  Vehicle detection with a part-based model for complex traffic conditions , 2013, Proceedings of 2013 IEEE International Conference on Vehicular Electronics and Safety.

[3]  P. Gamba,et al.  A fast algorithm for target shadow removal in monocular colour sequences , 1997, Proceedings of International Conference on Image Processing.

[4]  Nick Efford,et al.  Digital Image Processing: A Practical Introduction Using Java , 2000 .

[5]  Hagit Hel-Or,et al.  Shadow Removal Using Intensity Surfaces and Texture Anchor Points , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[6]  John B. Shoven,et al.  I , Edinburgh Medical and Surgical Journal.

[7]  Andrew Blake,et al.  An HMM-Based Segmentation Method for Traffic Monitoring Movies , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Sei-Wang Chen,et al.  Shadow detection and removal for traffic images , 2004, IEEE International Conference on Networking, Sensing and Control, 2004.

[9]  S. M. Mahbubur Rahman,et al.  Detection and Classification of Vehicles From Video Using Multiple Time-Spatial Images , 2012, IEEE Transactions on Intelligent Transportation Systems.

[10]  Van-Dung Hoang,et al.  Localization and tracking of same color vehicle under occlusion problem , 2012, 2012 9th France-Japan & 7th Europe-Asia Congress on Mechatronics (MECATRONICS) / 13th Int'l Workshop on Research and Education in Mechatronics (REM).

[11]  Yu Liu,et al.  Real-time detection of traffic flow combining virtual detection-line and contour feature , 2011, Proceedings 2011 International Conference on Transportation, Mechanical, and Electrical Engineering (TMEE).

[12]  Oihana Otaegui,et al.  Adaptive Multicue Background Subtraction for Robust Vehicle Counting and Classification , 2012, IEEE Transactions on Intelligent Transportation Systems.