A CAD driven multiscale approach to automated inspection - Maciejewski, Anthony A., author; Khawaja, Khalid W., author; Bouman, Charles Addison, author; Tretter, Daniel, author; IEEE, publisher (Colorado State University. Libraries, 1994)
In this paper we develop a general multiscale stochastic object detection algorithm for use in an automated inspection application. Information from a CAD model is used to initialize the object model and guide the training phase of the algorithm. An object is represented as a stochastic tree, where each node of the tree is associated with one of the various object components used to locate and identify the part. During the training phase a number of model parameters are estimated from a set of training images, some of which are generated from the CAD model. The algorithm then uses a fast multiscale search strategy to locate and identify the subassemblies making up the object tree. We demonstrate the performance of the algorithm on a typical mechanical assembly.
Keywords: mechanical engineering computing; object detection; stochastic processes; CAD; automatic optical inspection; image resolution; parameter estimation; mechanical engineering