Rj. Recknagel et al., High-resolution defect detection and noise reduction using wavelet methodsfor surface measurement, J OPT A-P A, 2(6), 2000, pp. 538-545
Nowadays the demands on quality control are constantly increasing, hence an
important step is a completely automated control with well defined risks.
Very promising solutions are optical 3D, in addition to surface measurement
. Here, an algorithm is presented to separate local defects from the surfac
e and the noise (measurement error and surface roughness) with a given manu
facturer's risk for piecewise smooth surfaces. The algorithm consists of a
feature enhancement by means of special wavelets and thresholding and inter
polation schemes to recover a defect- and noise-free surface and subsequent
ly the extension and shape of the defects in all directions with reduced ra
ndom errors. The limits of the algorithm such as accuracy, sensitivity, max
imum cover rate of the surface with defects and rotation and translation in
variance are shown theoretically and by numerical simulations. Experimental
ly, nanoindents are measured by means of confocal microscopy, and a reducti
on of the random errors by one order of magnitude is observed. Furthermore,
a ceramic plate is measured by means of fringe projection and features are
detected which are much smaller than the noise. Finally, a white light mea
surement is evaluated to demonstrate the scale and instrument independence
of the method.