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This paper presents an automatic road traffic control and monitoring system for day time sequences using a B & W camera. Important road traffic information such as mean speed, dimension and vehicles counting are obtained using computer vision methods. Firstly, moving objects are extracted from the scene by means of a frame-differencing algorithm and texture information based on grey scale intensity. However, shadows of moving objects belong also to the foreground. Shadows are removed from the foreground objects using top hat transformations and morphological operators. Finally, objects are tracked in a Kalman filtering process, and parameters such as position, dimensions, distance and speed of moving objects are measured. Then, according to these parameters moving objects are classified as vehicles (trucks or cars) or nuisance artifacts. For results visualization, a 3D model is projected onto vehicles in the image plane. Some experimental results using real outdoor sequences of images are shown. These results demonstrate the accuracy of the proposed system under daytime interurban traffic conditions.