1. College of Electric Engineering, Yanshan University, Qinhuangdao, Hebei 066004, China
2. The First Mine of the Third Oil Plant, Daqing Oil Field, Daqing, Heilongjiang 163000, China
Abstract A moving vehicle detection method was proposed, which is based on computer vision for vehicle detection in video image. First, the best variance parameters were selected and the bilateral filtering is used for image pre-processing. Then the real-time background image is updated with surendra background updating algorithm, using the particle swarm optimization (PSO) maximum entropy method to obtain background subtraction image threshold. Next, the binary image will be handled by morphology processing and the moving vehicles will be detected. Experimental results show that the algorithm is not only suitable for a simple background with slow-speed cars, but in a complex situation with larger noise and fast-speed cars, the proposed method can detect moving vehicles accurately through the adverse effect of the external environment. Hence, the accuracy of detection was improved.
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2017, Vol. 38 
