Abstract: In order to enhance the edge features of pipeline weld magnetic flux leakage image, an edge enhancement method based on Laplace and multi⁃scale mathematical morphology was proposed. Firstly, magnetic flux leakage data of pipeline magnetic flux leakage internal detector are collected for imaging, Then, using mathematical morphology algorithm, we construct multi⁃scale structural elements to detect the edge of the image, and use edge color constraints to delete non⁃edge points. Finally, edge is enhanced by Laplace operator. The results show that the method can accurately extract the weld and defect boundaries of the magnetic flux leakage signal image, and effectively separate the weld and defect. It has certain feasibility and practicability.

Key words: Magnetic flux leakage image, Laplacian, Mathematical morphology, Edge color constraint pairs, Edge enhancement

摘要： 为增强管道焊缝漏磁图像的边缘特征，提出一种基于Laplacian与多尺度数学形态学的焊缝漏磁图像边缘增强方法。首先采集管道漏磁内检测器中的漏磁数据进行成像，然后利用数学形态学算法，通过构建多尺度结构元素对图像进行边缘检测，利用边缘颜色约束对删除非边缘点，最后利用拉普拉斯算子对边缘进行增强。结果表明，该方法可较准确地提取漏磁信号图像的焊缝和缺陷边界，实现焊缝和缺陷的边缘增强，具有一定的可行性和实用性。

关键词: 漏磁图像, Laplacian, 数学形态学, 边缘颜色约束对, 边缘增强