Traffic accidents are frequent nowadays. The high frequency of accidents may be because drivers do not pay enough attention to other vehicles or environmental conditions. In particular, the fact that a driver cannot see vehicles in the blind spot can cause accidents. Therefore, this thesis develops a driving assistance system based on computer vision. The system main function is to help the driver to identify the vehicles from the environment-related information. Vehicles move quickly on the highway, often approaching speeds of over 100km/h. Therefore, accidents can easily occur if drivers do not pay attention. The reaction time is often extremely short. The proposed system can identify vehicles at a distance of 30–50m, providing a driver with information about vehicles in the current environment, and enhancing the driver reaction time. Therefore, the system processing time must not exceed 0.98 seconds. However the system may process 20–40 frames in a second. A processing cycle can thus be completed in 20–50ms. The system includes both land detection and vehicle detection. The land and the vehicles detection use the basic image processing methods, which contains the gray scale, binary and region processing function. Finally, the original video image is mapped to be a vertical view displayed on the driver’s screen.
