Abstract

The statistical properties of speckle patterns generated from a rough surface under a fully developed static speckle-pattern illumination are examined. The roughness dependence of the intensity autocorrelation function is studied and utilized to characterize typical engineering surfaces with anisotropic roughness. The speckle patterns under investigation are recorded by use of a CCD technique and are then analyzed by digital image processing algorithms to obtain a parameter that describes the surface roughness. It is shown that an in-process surface inspection can be achieved by this method.

© 1999 Optical Society of America

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