关键词: 铁路运输, 视觉检测, 逆透视映射, 轨道提取, 单应矩阵, Chamfer距离变换

Abstract:

This paper introduces an approach that extracts rail track by matching the edge features of the real image to the candidate rail patterns which is parameterically modeled, and the geometric constraints of the rail pattern are taken into consideration during the pattern generation. To address the challenge posed by the open environment, we assume the top surfaces of the pair rails are located in a virtual plane, and a homography matrix can be used to describe the geometry relationship between the virtual plane and the camera image plane. Then based on inverse projective mapping (IPM), the whole image is divided into several sections along the vertical direction. In each section, the rail pair can be approximated by two parallel line segmentations. Based on the prior geometric constraints, candidate rail patterns are generated and the rail track recognition is modeled as a 2D searching process. Some prior knowledge is used for robust detection. The rail track extraction in the whole IPM image is obtained by integrating the results of each section. During this integration stage, a curve fitting is applied and statistics of some parameters, such as the direction and position of the line segments can be adopted to remove the noise results from each section. The fitting curve is converted back to the original grey image. Experiments with on-site image show the performance of the proposed approach.

Key words: railway transportation, visual inspection, inverse projective mapping (IPM), rail track extraction, homography matrix, chamfer distance transformation