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Comparison between 3D Digital and Optical Microscopes for the Surface Measurement using Image Processing Techniques

机译:使用图像处理技术进行3D数字和光学显微镜的比较

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Surface Engineering has been a scientific discipline studying various procedures for the improvement of surface properties since 1980. The surface roughness of manufactured parts is commonly measured by the tactile methods. The stylus profilometer is one of the standard techniques assessing surfaces. This is a worthy method for looking at small areas but the major disadvantage of using a stylus profilometer is that it requires direct physical contact limiting the measuring speed. In contrast to contact measurement systems, optical technique, which is a non-destructive and non-contact method, appears to be a proper alternative for performing measurement of surface quality including surface roughness. The optical measurement instruments were used for the experiments. One of them was based on the "Focus Variation" technology and the other one was the confocal laser scanning microscope. In this study, 3D digital microscope in addition to the optical microscopes was used. The aim of this study is to compare each technique with others. In this study, the surface roughness were evaluated by employing the image processing methods such as line scanning, speckle and fast fourier transform (FFT) with three different samples machined via different manufacturing processes. The surface roughness results from processed images were obtained using flexible image analysis techniques such as Dark-light technique developed by the authors. The values calculated with the proposed method were compared with the roughness values obtained from 3D digital and optical microscopes.
机译:表面工程一直是一种科学学科,从1980年以来,研究了各种程序。制造部件的表面粗糙度通常通过触觉方法测量。触控笔Profilecometer是评估表面的标准技术之一。这是一种值得看小区的有价值的方法,但使用触控笔轮廓仪的主要缺点是它需要直接的物理接触限制测量速度。与接触测量系统相比,作为非破坏性和非接触方法的光学技术似乎是用于执行包括表面粗糙度的表面质量的测量的适当替代方案。光学测量仪器用于实验。其中一个基于“焦距变化”技术,另一个是共聚焦激光扫描显微镜。在该研究中,使用除光学显微镜之外的3D数字显微镜。本研究的目的是将每种技术与他人进行比较。在这项研究中,通过采用通过不同制造工艺加工的三种不同样品的线扫描,散斑,快速傅立叶变换(FFT)等图像处理方法来评估表面粗糙度。使用柔性图像分析技术获得处理图像的表面粗糙度,例如作者开发的深色技术。将用所提出的方法计算的值与从3D数字和光学显微镜获得的粗糙度值进行比较。

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