Visual inspection of machined parts

Abstract

A CAD-model-based machine vision system for dimensional inspection of machine parts is described, with emphasis on the theory behind the system. The original contributions of this work are: (1) the use of precise definitions of geometric tolerances suitable for use in image processing, (2) the development of measurement algorithms corresponding directly to these definitions, (3) the derivation of the uncertainties in the measurement tasks, and (4) the use of this uncertainty information in the decision-making process. Initial experimental results have verified the uncertainty derivations statistically and proved that the error probabilities obtained by propagating uncertainties are lower than those obtainable without uncertainty propagation.<>