基于数字图像处理的表面粗糙度检测

The Surface Roughness Detection Based on Digital Image Processing

针对传统表面粗糙度测量仪系统的可靠性不高,模拟信号的误差较大且不便于处理,测量不准确等问题,提出了一种基于机器视觉的表面粗糙度检测的新方法:首先利用CCD进行采样,提取金属工件的表面图片,通过OpenCV软件处理编程计算,对图片进行数字化预处理(灰度化,降噪,滤波等),提取图片中的纹理特征,最终计算得出表面粗糙度数值,并且与传统的触针法检验结果做对比,证明方法的可行性,比其他的测量表面粗糙度的方法更加高效,准确。

Aiming at some problems of traditional surface roughness measuring instrument,such as the system’s reliability is not high,the error of the analog signal is miraculous,and not easy to deal with,the measurement is not accurate and so on.In this paper,a new way of surface roughness detection based on machine vision is proposed.First,CCD machine is used to sampling and surface images of metal work pieces are extracted.Second,after the images processed(gray,noise reduction,wave filtering,etc.)and program calculation is carried out for images through the OpenCV software,then the texture feature of the images is extracted and finally the surface roughness value is calculated.Compared with test results of the traditional stylus method,it proves that the method is feasible,and more efficient and accurate than other surface roughness degree test method.