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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