建筑钢结构进展2023，Vol.25Issue(12)：85-93,101,10.DOI:10.13969/j.cnki.cn31-1893.2023.12.009
基于计算机视觉的钢构件防腐涂层缺陷检测
Defect Identification of Anti-corrosive Coating of Steel Members Based on Computer Vision
王亦君 1蒋首超2
作者信息
- 1. 同济大学土木工程学院,上海 200092
- 2. 同济大学土木工程学院,上海 200092||同济大学土木工程防灾国家重点实验室,上海 200092
- 折叠
摘要
Abstract
Steel structures are widely used in building constructions,but the corrosion resistance of steel is not satisfying.Corrosion will reduce the load-bearing capacity of the steel members,even affecting the safety of the structure.Periodical inspection and maintenance of the anti-corrosive coating of steel members is one of the most important methods to ensure the coating's effectiveness.In order to automatically detect and classify surface defects in the anti-corrosive coating of steel members,a computer vision detection method based on image processing technology and the Support Vector Machine(SVM)algorithm was proposed.In the image processing stage,adaptive median filtering and image enhancement are applied to the gray-scale defect image.Then the Otsu thresholding method and Canny operator were used to segment the enhanced images.In the feature extraction stage,65-dimensional features including simple geometric features,invariant moment features,projection features,and texture features of the images were extracted.The Fisher criterion was used to select the 37 most contributing features.The eigenvectors were used as input to develop a multi-classification model based on the SVM algorithm,achieving a recognition rate of 95.83％.The proposed method can effectively detect and identify the surface defects in the anti-corrosive coating of steel structural members.关键词
计算机视觉/防腐涂层/缺陷检测/特征提取/支持向量机Key words
computer vision/anti-corrosive coating/defect detection/feature extraction/SVM分类
建筑与水利引用本文复制引用
王亦君,蒋首超..基于计算机视觉的钢构件防腐涂层缺陷检测[J].建筑钢结构进展,2023,25(12):85-93,101,10.
