Vehicle detection and tracking method - Suzana, Mohamed Salleh (2019)
Traffic surveillance system or as known as Intelligent Transportation System (ITS) is an important issue in traffic monitoring management. A computer-vision based technique is the one of the most popular methods applied in video surveillance application. Several techniques of vehicle detection, classification, counting and tracking have been proposed by many researchers. Therefore, the existing techniques that have been used now still have an issue regarding to lowest quality of the traffic monitoring systems and sometimes low on their effectiveness and accuracy. Focus on vehicle detection and tracking system, Optical flow is used in order to detect and track vehicles. Kalman filter is the popular object tracking method implement in current existing system, however, Optical flow based method give better performance result rather than kalman filter based on the research analysis that have been done. While, for foreground detection method, the frequently used method is Background subtraction method approach but in this research, more focusing on Adaptive Background subtraction. This research objective is to develop Vehicle Detection and Tracking System and to enhance its accuracy using Adaptive Background subtraction with Adaptive Median Filter to filter the noise distortion in the acquired video. The proposed methods come from comparison analysis of existing method focusing on noise filtering which is Median filter and Adaptive Median filter that will give satisfied result for the vehicle’s detection accuracy.