Surface Roughness Evaluation of Milled Surfaces by Image Processing of Speckle and White-Light Images

摘要

An experimental approach for surface roughness measurement based on the speckle images caused by a laser beam on the milled surfaces and the white-light images of the same surfaces is presented. Since the surface slope at every point of the surface influences the speckle pattern, the surface roughness parameters R_(da) and R_(dq) were used for comparison. A CMOS camera, LASER and LED light sources were used for capturing speckle and white-light images of the milled surfaces. From the image pixel intensity matrix, a signal vector was generated and was used for the image metric. It is found that standard deviation and mean of the image signal vector correlate well with R_a, R_(da) and R_(dq) values measured by a standard Taylor Hobson surface roughness tester. The correlation was found to be better for speckle images than the white-light images.