Abstract
An immense interest of the researchers in real time vehicle detection, tracking and counting is a need of society for trouble free and safer travelling in cities. Automatic tracking and detection of vehicles is a laborious task in traffic monitoring. The proposed method processes an input video to track and detects the vehicle through its motion and also counts the total number of vehicles on the road. To enhance the process, we use consolidation of different image processing and computer vision techniques. The proposed method of detection and tracking of vehicles on a road has been implemented on hardware raspberry Pi 3B using MATLAB as software for the simulation. The video is captured on the M4 motorway in Pakistan by a camera attached with raspberry pi then it is processed through the proposed algorithm. The Gaussian Mixture Model (GMM) along with optical flow parameters are used to detect vehicles which are in motion. To segment objects from the background vector threshold is used. The filtering process is applied to suppress the noise and then blob analysis is used to identify the vehicles from an input video. The outcomes demonstrate that the proposed framework effectively distinguishes and tracks moving objects in the urban recordings.
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Ansari, A., Khan, K.B., Akhtar, M.M., Younis, H. (2019). Vehicle Detection, Tracking and Counting on M4 Motorway Pakistan. In: Bajwa, I., Kamareddine, F., Costa, A. (eds) Intelligent Technologies and Applications. INTAP 2018. Communications in Computer and Information Science, vol 932. Springer, Singapore. https://doi.org/10.1007/978-981-13-6052-7_36
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DOI: https://doi.org/10.1007/978-981-13-6052-7_36
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