Enhanced Edge Detection for 3D Crack Segmentation and Depth Measurement with Laser Data

Abstract

With the usage of computer visual technology in civil engineering, pavement crack survey with imaging sensor gained wide attention in the past years. Unfortunately, it is still a challenge to achieve the satisfying results. This paper presents a pavement crack survey approach based on edge detection for laser data. At first, the LS-40 line-laser scanner is implemented to achieve 3D pavement surface data. With the advantage of the various depth information exhibited in the pavement data, an enhanced edge detection based on fractional differential is proposed for 3D crack segmentation. The proposed method could effectively enhance the crack boundary and maintain texture details, which can guarantee the high accuracy in crack segmentation. Moreover, a novel plane fitting method based on dynamic threshold is studied to calculate crack depth information. It can not only identify and remove invalid points effectively, but also accomplish plane calculation with errors in three directions. Experiments verify that the proposed approach can achieve the satisfying result and can work well in F-measure system.