Automatic Crack Detection in Built Infrastructure Using Unmanned Aerial Vehicles

TL;DR

This paper presents an automated method for crack detection in infrastructure using UAVs, combining 3D modeling, image stitching, and histogram analysis to improve inspection efficiency and safety.

Contribution

It introduces a fully automated UAV-based crack detection system utilizing 3D models and histogram analysis, enhancing inspection speed and safety compared to manual methods.

Findings

Automated crack detection reduces inspection time.

System effectively identifies potential cracks.

Experimental results validate the approach.

Abstract

This paper addresses the problem of crack detection which is essential for health monitoring of built infrastructure. Our approach includes two stages, data collection using unmanned aerial vehicles (UAVs) and crack detection using histogram analysis. For the data collection, a 3D model of the structure is first created by using laser scanners. Based on the model, geometric properties are extracted to generate way points necessary for navigating the UAV to take images of the structure. Then, our next step is to stick together those obtained images from the overlapped field of view. The resulting image is then clustered by histogram analysis and peak detection. Potential cracks are finally identified by using locally adaptive thresholds. The whole process is automatically carried out so that the inspection time is significantly improved while safety hazards can be minimised. A prototypical system has been developed for evaluation and experimental results are included.