A fuzzy vehicle detection based on contour size similarity

In this paper, the obstacle detection for autonomous vehicle is carried out by a monocular camera, which is capable of detecting multiple obstacles, identifying the difference between obstacles and text or shadows on the road surface. The task of detection can be fulfilled under the circumstances of general brightness or in the presence of strong sunshine. An obstacle detection approach named contour size similarity (CSS) is developed in this paper. CSS is a way to make use of the contour size of objects and compare the similarity between objects and obstacles detected by means of fuzzy so as to judge whether the objects in the images are the obstacles we want to detect. The obstacles in this paper mainly refer to vehicles. Vehicles and obstacles with similar contour of vehicles can be detected by CSS. Then, we use section division to find out the nearest obstacle in separate section to provide necessary information for autonomous vehicles.