基于图像处理的港机钢结构喷涂缺陷检测研究

Research on Spraying Defect Detection of Port Machinery Steel Structure Based on Image Processing

为了保障港机钢结构表面防护的涂装质量,本文对港机钢结构表面的喷涂缺陷进行了检测研究。首先设计构件喷涂缺陷检测试验,建立样本数据集;然后结合图像形态学特征,应用改进Canny算法提高特征边缘检测效果;选取周长、面积和相关性等数据作为分类的阈值条件,实现5种涂膜缺陷分类。实际结果表明,该方法可有效检测并识别喷涂缺陷类别。

To ensure the coating quality of the port machinery,the spraying defects on the surface of the steel structure of port machinery were detected and studied in this paper.Firstly,the component spraying defect detection test is designed,and the sample data set is established;Then,combined with,the morphological features of the image,the improved Canny algorithm is applied to improve the.detection effect of feature edges.The data such as circumference,area and correlation were selected as the threshold conditions for classification,and five kinds of coating defect classification were realized.The actual results show that the proposed method can detect and identify the spray defect category more effectively.