The multi-level shadow classification has been shown to provide reliable information on the presence of vehicles in traffic scenes. The method is based on classifying the shadow shapes into six categories at each threshold level. Non-overlapping shadow shapes with higher priority are selected at each level. Shadow-reshaping capability makes the resulting shadow information robust to the variation of operating conditions. Unlike other approaches, vehicle movement information between frames is not utilized; thereby the traffic parameters can be measured quantitatively even when the vehicle movement is not observed. Also the detecting performance is not affected by the abrupt change of weather because background information is not utilized.