| With the steady growth of world economy and the continuous decline in car prices in recent years, the holdings of private cars increased significantly. By enjoying the convenience taken form the car, the problems due to traffic accidents also have become increasingly prominent.30 percent of accidents are caused by car's back blind spot when drivers parking. Therefore, it is essential to identify the surrounding environment's useful information accurately. However, most of the existing parking assist products are based on radar or ultrasonic sensors, it has several weak points, such as small detection area, blind spots, having a bad performance in detecting pedestrians, especially children and other small objects. Taking the cost, power consumption, equipment installation, camera demarcating into account, obstacle detection system based on the combination of monocular vision and ultrasonic sensors or radar is direction of development in the future.This paper presents an obstacle detection algorithm based on combination of motion compensation and feature information, this algorithm is based on monocular vision. This algorithm estimates the motion parameters of the camera between two neighboring images, then makes the motion compensation, and generates a virtue image and a difference image, and then according to several rules extracts the candidate obstacle regions from the current image using the information provided by the virtue image and the difference image. Finally, this algorithm filters the candidate obstacle regions using the obstacle features:vertical edge line and region feature in a image, then determines the obstacle regions.The results show that the algorithm can support assisting backover in complex scenes, achieve the robust obstacle detection in any shape, any size and no mater it is shop or not, such as vehicles, pedestrians, ball, poles and so on, provides an important basis for avoid collision algorithm in assist park system. |
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