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Traffic congestions and traffic jams are major challenges in some cities due to the substantial surge in the population and the number of cars. Thus, controlling the traffic density on roads and highways is essential. In this paper, we explore a method that can be used to direct traffic. This method is based on image processing and comparing two images with and without cars. At first, the foreground of the image is obtained. Then the road is partitioned to calculate the area occupied by a car in each part of the road. After that, the number of cars is estimated through dividing the total area of cars by that of a typical car. The camera angle and road distance from the camera are two essential factors in this method. Therefore, it is vital to use a fixed camera in this method. This proposed model was tested with the GRAM-RTM dataset and exhibited an average accuracy of 95%.