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Proceedings Paper

Image understanding algorithms for remote visual inspection of aircraft surfaces
Author(s): Priyan Gunatilake; Mel Siegel; Angel G. Jordan; Gregg W. Podnar
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Paper Abstract

Visual inspection is, by far, the most widely used method in aircraft surface inspection. We are currently developing a prototype remote visual inspection system, designed to facilitate testing the hypothesized feasibility and advantages of remote visual inspection of aircraft surfaces. In this paper, we describe several experiments with image understanding algorithms that were developed to aid remote visual inspection, in enhancing and recognizing surface cracks and corrosion from the live imagery of an aircraft surface. Also described in this paper are the supporting mobile robot platform that delivers the live imagery, and the inspection console through which the inspector accesses the imagery for remote inspection. We discuss preliminary results of the image understanding algorithms and speculate on their future use in aircraft surface inspection.

Paper Details

Date Published: 15 April 1997
PDF: 12 pages
Proc. SPIE 3029, Machine Vision Applications in Industrial Inspection V, (15 April 1997); doi: 10.1117/12.271231
Show Author Affiliations
Priyan Gunatilake, Carnegie Mellon Univ. (United States)
Mel Siegel, Carnegie Mellon Univ. (United States)
Angel G. Jordan, Carnegie Mellon Univ. (United States)
Gregg W. Podnar, Carnegie Mellon Univ. (United States)


Published in SPIE Proceedings Vol. 3029:
Machine Vision Applications in Industrial Inspection V
A. Ravishankar Rao; Ning S. Chang, Editor(s)

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