A Detecting Method for Structure Crack Edges of Municipal Railway Tunnels under Supervised Learning

Abstract

Regular inspection of crack diseases was the key to ensure the normal operation of metro tunnel structures. To address this issue, a method for crack detection of metro tunnel structures under supervised learning was proposed herein. Firstly, the images of the metro tunnel structures were obtained by a consumer digital camera. Secondly, the geometric feature vectors of the edge targets were constructed based on the preliminary detection results by Canny operator, and then the crack edges of metro tunnel structures were detected by using the geometric feature vectors of edge targets. Finally, the effectiveness of the proposed method was verified by the image data of the metro tunnel structures.