Image Understanding Algorithms for Remote Visual Inspection of Aircraft Surfaces
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.
BibTeX
@conference{Gunatilake-1997-14303,author = {Priyan Gunatilake and Mel Siegel and Angel Jordan and Gregg Podnar},
title = {Image Understanding Algorithms for Remote Visual Inspection of Aircraft Surfaces},
booktitle = {Proceedings of SPIE Machine Vision Applications in Industrial Inspection V},
year = {1997},
month = {February},
volume = {3029},
pages = {2 - 13},
}