In this paper an approach to traffic analysis is presented which employs image processing techniques to detect non-conforming behavior of vehicles on roadways in addition to providing the normal traffic statistics required for traffic monitoring. Traffic scenes recorded on video tape were used in the laboratory to test the approach. Binary images were obtained by subtracting each incoming sampled frame from a reference frame and thresholding the result. Centroids were calculated for each of the objects found in the binary images and were used to track the path of each vehicle on successive frames for its duration along the roadway in the region of interest. To minimize the computation time required to match objects from a given frame to the corresponding objects in the next frame, the velocity of each vehicle and inertial constraints on speed and angular deviation were used to predict each object's location in the next frame. The object nearest the target value was chosen as the appropriate match. The trajectory of each vehicle was checked for conformity. The implementation of the approach has been able to identify non-conforming vehicle behavior and issue a message on the monitor describing the detected behavior.