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Proceedings Paper

Mathematical Morphology and Its Application in Machine Vision
Author(s): David G. Daut; Dongming Zhao
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Paper Abstract

Mathematical morphology provides an efficient tool for image analysis. We study the problem of flaw detection in materials which are represented by very poor contrast digital images. An algorithm for flaw detection in the case of glass matte surfaces has been developed. The object skeletons within the binary images are obtained and directional connectivity information in the skeletons is used to discriminate noise patterns from flaws according to a specified criteria. After the discrimination process, the remaining skeletons correspond to flaws and can be employed to recover the shape of flaws. An alarm flag may be turned on if the sizes of the detected flaws are found to exceed industrial standards. In the case of a grayscale image, the image is converted to a binary version by using an adaptive threshold algorithm, then the algorithm for binary images is applied. Experimental results have been obtained for both binary and grayscale digital image data.

Paper Details

Date Published: 1 November 1989
PDF: 11 pages
Proc. SPIE 1199, Visual Communications and Image Processing IV, (1 November 1989); doi: 10.1117/12.970030
Show Author Affiliations
David G. Daut, Rutgers University (United States)
Dongming Zhao, Rutgers University (United States)

Published in SPIE Proceedings Vol. 1199:
Visual Communications and Image Processing IV
William A. Pearlman, Editor(s)

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