BARTIN applied to visual inspection of axisymmetric engineering parts

A visual inspection scheme for detecting flaws in axisymmetric engineering parts is described and shows very good performance. The scheme can be used for both recognition of parts and classifying flaws. The polygon transform, a compact representation of the edge information in images of axisymmetric objects gives the inspection system invariance with respect to location, scale, orientation, and illumination intensity. Polygon transform representations of the object provide the inputs to a BARTIN (Bayesian Real Time Network) that generates the inspection decisions. This implementation employs a distance measure related to Kullback-Leibler divergence to quantify the difference between sample polygon transforms, and demonstrates the parsimony and reliability of the BARTIN architecture. The latter enables inclusion of prior information in the form of probabilities, decision utilities, and engineering drawings. The results obtained from an application provided by British Aerospace gave two wrong (but safe) decisions in 625 test examples