A robust geometric model of road extraction method for intelligent traffic system

Abstract

In the intelligent transportation system, the geometry for the street is an important factor in vehicle monitoring. It helps to point out areas of interest, reduce computing costs, increased accuracy in detecting and identifying objects and facilitate data collection. In this paper, a new robust method of extracting the geometric model of the road is presented. The method is based on vehicle motion data to show the exact shape of the street without depending on the edge elements. First, the special features of consecutive frames are extracted and matched together. Second, by stretching the lines from matching these respective keypoints, intersections are indicated. The vanishing point is achieved by calculating the center of these intersections. Third, combining the infinity and the extremes of the motion data to tangent to the boundary of the geometry. Finally, by charting the area with the greatest matching ratio between the keypoints in the adjacent frame we reach the area of interest. Vietnam traffic dataset is used to verify the effectiveness and accuracy of the proposed method. Experimental results show that the proposed method has shown the correct geometry of the path. The use of motion data is a sustainable method of extracting Vanishing Point without being affected by other side effects.