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Proceedings Paper

Identification of flaws in metallic surfaces using specular and diffuse bispectral light sources
Author(s): Michael Magee; Steven B. Seida; Ernest A. Franke
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Paper Abstract

A computer vision based automated method for identifying and quantifying flaws in cast metal parts is presented. The specific defects to be isolated consist of small circular concavities in the surface (pits) and larger isolated regions (scratches) that may have been abraded due to cutting or handling operations. The approach taken identifies these anomalous features using two spatially separated light sources with different spectral characteristics to produce highly specular illumination at one wavelength and shallow diffuse illumination at a different wavelength. A bispectral image is processed to yield the sought flaws. This processing consists of identifying regions of interest in the original image that may contain potential flaws and applying a morphological region labelling operation to extract candidate pits and scratches. Geometric constraints are applied to the extracted regions in order to isolate the true flaws. The discussion that follows details the algorithmic approach used to identify flaws as well as characterizing the results obtained.

Paper Details

Date Published: 1 November 1992
PDF: 14 pages
Proc. SPIE 1825, Intelligent Robots and Computer Vision XI: Algorithms, Techniques, and Active Vision, (1 November 1992); doi: 10.1117/12.131553
Show Author Affiliations
Michael Magee, Univ. of Wyoming (United States)
Steven B. Seida, Southwest Research Institute (United States)
Ernest A. Franke, Southwest Research Institute (United States)

Published in SPIE Proceedings Vol. 1825:
Intelligent Robots and Computer Vision XI: Algorithms, Techniques, and Active Vision
David P. Casasent, Editor(s)

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