磁瓦表面夹层缺陷的检测和识别方法

为了改变目前以目视为主的磁瓦缺陷检测现状,应用计算机视觉技术检测与识别磁瓦缺陷.首先,应用图像剪切技术获得需要检测的部分;然后,应用Laplacian算子和Wiener滤波器进行图像锐化和滤波去噪,选择相应的阈值进行图像二值化;最后根据白色区域的面积和周长与给定的阈值进行比较,实现夹层缺陷的检测.MATLAB仿真实验验证了算法的有效性.

A Study of the Detection of the Interlayer Surface Defect of Arc-magnets

computer To change the prae vision technology tice of detecting the surface should be applied. First, image-cutting techniques; then, sharpen and filter the Wiener filter, and binarize the image with the proper defects of a obtain the image with threshold; a rc-magnets by the naked eye, the parts to be detected using the the Laplacian operator and the nd lastly, compare the area and circumference of the white arc-magnet with the given threshold value and realize the detection of the interlayer defect. Good defect detection and identification is achieved through the MATLAB simulation experiments.