The image processing technique is very sensitive to the variation of external environment, so it tends to lose a lot of accuracy when the external environment changes rapidly. In this paper, we propose a vehicle detecting and tracking system for crime prevention suitable for an external environments with various changes using the image processing technique. Because the vehicle camera detector for crime prevention extracts and tracks the vehicle within one lane, it is important to classify a characteristic region rather than the contour of a vehicle. The proposed system detects the entrance of the vehicle using optical flow and tracks the vehicle by classifying the headlights, the bonnet, the front-window and the roof area of the vehicle. Experimental results show that the proposed method is robust to the environmental changes such as type, speed and time of a vehicle.