Cracks Detection and Quantification Based on YOLOv8
Regular detection of structural cracks is crucial for ensuring structural safety.Currently,traditional manual inspection methods are time-consuming and labor-intensive,and it is difficult to quan-tify the size of cracks.To address these issues,a method based on YOLOv8 for detecting and quantif-ying cracks was proposed,aiming to improve detection efficiency and achieve quantitative crack analysis.The YOLOv8 algorithm was utilized to segment crack images,and the pixel count was extracted from the segmented crack images.Additionally,the real geometric features of cracks were computed based on the scale factors obtained from actual measurements.The results demonstrate that the segmentation accuracy of YOLOv8 exceeds 85％,and the error percentage of quantified crack features is less than 4％in experimental tests,with a maximum goodness of fit of 0.985 8.The proposed method holds promise for providing a prospective solution for structural crack detection.
structural cracksYOLOv8image processinggeometric features
万方数据
维普
