Lu Rong-Sheng, Tian Gui-Yun, Gledhill Duke, Ward Steve
School of Instrument Science and Opto-electronic Engineering, Hefei University of Technology, China.
Appl Opt. 2006 Dec 10;45(35):8839-47. doi: 10.1364/ao.45.008839.
Surface speckle pattern intensity distribution resulting from laser light scattering from a rough surface contains various information about the surface geometrical and physical properties. A surface roughness measurement technique based on the texture analysis of surface speckle pattern texture images is put forward. In the surface roughness measurement technique, the speckle pattern texture images are taken by a simple setup configuration consisting of a laser and a CCD camera. Our experimental results show that the surface roughness contained in the surface speckle pattern texture images has a good monotonic relationship with their energy feature of the gray-level co-occurrence matrices. After the measurement system is calibrated by a standard surface roughness specimen, the surface roughness of the object surface composed of the same material and machined by the same method as the standard specimen surface can be evaluated from a single speckle pattern texture image. The robustness of the characterization of speckle pattern texture for surface roughness is also discussed. Thus the surface roughness measurement technique can be used for an in-process surface measurement.
由粗糙表面的激光散射产生的表面散斑图案强度分布包含有关表面几何和物理特性的各种信息。提出了一种基于表面散斑图案纹理图像纹理分析的表面粗糙度测量技术。在表面粗糙度测量技术中，散斑图案纹理图像由一个简单的设置配置拍摄，该配置由一台激光器和一台电荷耦合器件（CCD）相机组成。我们的实验结果表明，表面散斑图案纹理图像中包含的表面粗糙度与其灰度共生矩阵的能量特征具有良好的单调关系。在用标准表面粗糙度试样对测量系统进行校准后，可以从单个散斑图案纹理图像中评估与标准试样表面由相同材料制成且采用相同方法加工的物体表面的表面粗糙度。还讨论了散斑图案纹理表征表面粗糙度的稳健性。因此，表面粗糙度测量技术可用于过程中的表面测量。
