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The relationships between laser speckle pattern texture features of grinding surface and surface roughness are
investigated. The laser speckle pattern texture images of surface roughness are taken by a simple setup. Gauss-Markov
random field (GMRF) model is a kind of texture model method which can describe probability model of gather of
texture and be able to capture the local contextual information in an image. Therefore, by modeling GMRF model the
laser speckle texture images of grinding surface are analyzed. Feature vectors of GMRF are calculated with different
neighbor sets. Texture features- Mean, Variance and Energy are extracted to characterize grinding surface roughness
from GMRF feature vectors. The relationships curves are drawn between the texture features and surface roughness. The
experiment results show that the surface roughness contained in the surface speckle pattern texture images has a good
monotonic relationship with texture features of GMRF model. This method can extract the surface roughness of the
object surface composed of the same material and machined by the same method as the standard specimen.
Lei Yang,Rongsheng Lu, andLiqiao Lei
"Grinding surface roughness measurement based on Gauss-Markov
random field model of laser speckle pattern texture", Proc. SPIE 7997, Fourth International Seminar on Modern Cutting and Measurement Engineering, 79971X (26 May 2011); https://doi.org/10.1117/12.888436
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Lei Yang, Rongsheng Lu, Liqiao Lei, "Grinding surface roughness measurement based on Gauss-Markov random field model of laser speckle pattern texture," Proc. SPIE 7997, Fourth International Seminar on Modern Cutting and Measurement Engineering, 79971X (26 May 2011); https://doi.org/10.1117/12.888436