A CAD driven multiscale approach to automated inspection
Date
1994
Authors
Maciejewski, Anthony A., author
Khawaja, Khalid W., author
Bouman, Charles Addison, author
Tretter, Daniel, author
IEEE, publisher
Journal Title
Journal ISSN
Volume Title
Abstract
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.
Description
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Subject
mechanical engineering computing
object detection
stochastic processes
CAD
automatic optical inspection
image resolution
parameter estimation
mechanical engineering