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This paper describes a vision-based vehicle detection system for a blind spot warning function. This detection system has been designed to provide ample performance as a driving safety support system, while streamlining the image processing algorithm so that it can be processed using the computational power of an existing ECU. The procedure used by the system to detect a vehicle in a blind spot is as follows. The system consists of four functional components: obstacle detection, velocity estimation, vertical edge detection, and final classification. In obstacle detection, a predicted image is generated under the assumption that the road surface is a perfectly flat plane, and then an object is detected based on a histogram that is created by comparing the predicted image and an actually observed image. The velocity of the object is estimated by tracking the histogram over time, assuming that both the object and the host vehicle are traveling in the same direction.