Displacement Measurement Based on UAV Images Using SURF-Enhanced Camera Calibration Algorithm

Abstract

Displacement is an important parameter in the assessment of the integrity of infrastructure; thus, its measurement is required in a multitude of guidelines or codes for structural health monitoring in most countries. To develop a low-cost and remote displacement measurement technique, a novel method based on an unmanned aerial vehicle (UAV) and digital image correlation (DIC) is presented in this study. First, an auxiliary reference image that meets the requirements is fabricated using the selected first image. Then, the speeded-up robust features (SURF) algorithm is introduced to track the feature points in the fixed areas. The least square algorithm is then employed to resolve the homography matrix of the auxiliary reference image and target images; then, the acquired homography matrices are utilized to calibrate the deviation caused by the UAV wobble. Finally, the integral pixel and sub-pixel matching of the DIC algorithm is employed to calculate the displacement of the target object. The numerical simulation results show that the proposed method has higher calculation accuracy and stability. The outdoor experiment results show that the proposed method has definite practicability.