<title>Nonlinear filter derived from topological image features</title>

A digital machine-inspection system is being developed at Oak Ridge National Laboratory to detect flaws on printed graphic images. The inspection is based on subtraction of a digitized test image from a reference image to determine the location, number, extent, and contrast of potential flaws. When performing subtractive analysis on the digitized information, two sources of errors in the amplitude of the difference image can develop: (1) spatial misregistration of the reference and test sample, or (2) random fluctuations in the printing process. Variations in printing and registration between samples will generate topological artifacts related to surface structure, which is referred to as edge noise in the difference image. Most feature extraction routines require that the difference image be relatively free of noise to perform properly. A novel algorithm has been developed to filter edge noise from the difference images. The algorithm relies on the a priori assumption that edge noise will be located near locations having a strong intensity gradient in the reference image. The filter is based on the structure of the reference image and is used to attenuate edge features in the difference image. The filtering algorithm, consisting of an image multiplication, a global intensity threshold, and an erosion/dilat ion, has reduced edge noise by 98% over the unfiltered image and can be implemented using off-the-shelf hardware.