Color Analysis Supporting a Traffic Flow Measurement Based on Optical Flow

• Autorzy: Pawlik P. , Bubliński Z. , Głowacz A.
• Języki publikacji: EN

Abstrakty

EN

The aim of this work was to develop an algorithm for estimating the waiting time of the cars stopped before the intersection in a traffic flow measurement system (based on optical flow), which does not require the generation of the background and allows to calculation in real time. The proposed method performs analysis in HSV color space - a mask generated from S component is applied to H component. In this way a background - an asphalt and horizontal whitespace - is eliminated. The result of this operation is combined with data from optical flow to detect the vehicles which should be tracked.

Słowa kluczowe

EN

HSV color space; S component; H component

• Wydawca: Instytut Telekomunikacji i Informatyki Uniwersytetu Technologiczno-Przyrodniczego w Bydgoszczy
• Czasopismo: Image Processing & Communications
• Rocznik: 2014
• Tom: Vol. 19, no. 2-3
• Strony: 45--49
• Opis fizyczny: Bibliogr. 7 poz.

Twórcy

autor

Pawlik P.

• AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, Department of Automatics and Biomedical Engineering

autor

Bubliński Z.

• AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, Department of Automatics and Biomedical Engineering

autor

Głowacz A.

• AGH University of Science and Technology, Faculty of Computer Science, Electronics and Telecommunications, Department of Telecommunications

Bibliografia

• [1] Aslani, S., Mahdavi-Nasab, H. (2013). Optical flow based moving object detection and tracking for traffic surveillance, International Journal of Electrical, Electronics, Communication, Energy Science and Engineering, 7(9), 789-793
• [2] Głowacz, A., Mikrut, Z., Pawlik, P. (2012). Video detection algorithm using an optical flow calculation method, International Conference on Multimedia Cmmunications, Services and Security, 128-129
• [3] Lien, C.C., Tsai, M.H. (2011). Real-Time Traffic Flow Analysis without Background Modeling, Journal of Information Technology and Applications, 5(1),
• [4] Ottlik, A., Nagel, H.H. (2008). Initialization of model-based vehicle tracking in video sequences of inner city intersections, International Journal of Computer Vision, 80(2) 211-225
• [5] Suganya, D.K., Malmurugan, N., Sivakumar, R. (2012). Efficient Foreground Extraction Based on Optical Flow and SMED for Road traffic analysis, International Journal of Cyber-security and Digital Forensics, 1(3), 177-182
• [6] Tian, B. et al. (2011). Video processing techniques for traffic flow monitoring: A survey, IEEE Conference on Intelligent Transportation Systems, 1103-1108
• [7] Zhang, Z. et al. (2011). A traffic flow detection system combining optical flow and shadow removal, Third Chinese Conference on Intelligent Visual Surveillance, 45-48