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High Precision Traffic Monitoring Alert System using Image Background Subtraction
Objective: Monitoring the road traffic is helpful to know about the traffic density of a particular location, which helps in redirecting the traffic when crowded. In this paper, traffic density is monitored and vehicle count is estimated using background subtraction algorithm. Methods: The proposed technique utilizes a novel Motion Detection and Running Gaussian Average (MDRGA) recursive technique. The frame is captured from the input video sequence and is transformed to 0 to 255 gray levels from RGB color mode. This conversion considers the RGB values for each pixel and yield the corresponding reflectance value proportional to the brightness percentage of that pixel. The edge detection is then performed on the gray converted by locating the pixels of the image that correspond to the edges. Findings: The proposed system detects motion by comparing sequential frames crossing an imaginary line marked in the reference frame. Thus, the traffic density is detected and the proposed method is found to be efficient in terms of cost, quality and accuracy. This algorithm fetches the input video quickly from camera or storage device, processes immediately and gives the count of vehicles. This proposed system avoids occlusion problems and gives better results. Applications/ Improvements: This algorithm is helpful to avoid traffic collisions at peak areas, to avoid accidents and to reach the destination on time. Thus, the proposed system finds its application in real time systems and provides risk free environment.
Background Subtraction, Motion Detection and Running Gaussian Average (MDRGA) Recursive Technique, Redirection, Vehicle Count.
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