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Proceedings Paper

Comparison of multiresolution morphological and Laplacian techniques for automated inspection
Author(s): Jeffrey M. Seaton; A. Lynn Abbott
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Paper Abstract

This paper concerns the analysis of images at multiple scales of spatial resolution. We describe and compare two methods of generating hierarchical image representations (called pyramids) which are based on changes in image resolution. The first of these methods utilizes the tools of mathematical morphology to derive image pyramids, while the second method is based on well known linear filtering techniques to create Gaussian and Laplacian pyramids. Both methods involve the successive remodel of high frequency components from an image so that an ordered sequence of low pass filtered, subsampled images results. It is also possible in each case to use differences of adjacent levels in a low-pass pyramid to generate a band-pass pyramid of images. The resulting hierarchy of images is well suited to such applications as automated industrial inspection, since components of interest can be expected to appear at particular levels of the hierarchy. A problem with the latter method is that image features are blurred by the linear smoothing. This drawback is not present in the former technique, which depends on nonlinear, set-theoretic transformations. This paper describes these two methods for generating image pyramids and compares the results of each in the inspection of a printed circuit board.

Paper Details

Date Published: 1 March 1992
PDF: 12 pages
Proc. SPIE 1708, Applications of Artificial Intelligence X: Machine Vision and Robotics, (1 March 1992); doi: 10.1117/12.58620
Show Author Affiliations
Jeffrey M. Seaton, NASA/Langley Research Ctr. (United States)
A. Lynn Abbott, Virginia Polytechnic Institute and State Univ. (United States)

Published in SPIE Proceedings Vol. 1708:
Applications of Artificial Intelligence X: Machine Vision and Robotics
Kevin W. Bowyer, Editor(s)

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