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Proceedings Paper

Semiautomatic x-ray inspection system
Author(s): Nandan G. Amladi; Michael K. Finegan; William G. Wee
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Paper Abstract

Inspection of industrial images can be a laborious task. Automating the inspection using image processing techniques works effectively only with an appropriate human interface. This paper describes a semi-automatic aircraft engine component motion registration system. Manual inspection of aircraft engine x-ray data was replaced by the use of several interactive programs running on a personal computer. This system allowed the inspector to digitize, process, tabulate, and document test image sequences without requiring image processing experience. The new environment also provided a digital replacement for the analog densitometer previously used, as well as enabling the extraction of digital templates of arbitrary size. Once two masks were selected, measurements could be performed by correlating the pair with a sequence of images, in a batch process. Calibrated measurement results were sent automatically to file, printer, or screen; hardcopy output of found templates, superimposed on individual test images was used for visual verification. Several image processing techniques for performing correlation were surveyed and three of them were implemented. Complexity, speed, and accuracy of each are presented. The methods implemented were direct normalized cross-correlation, hierarchical normalized spatial cross-correlation, and Fourier transform based cross-correlation (using an array processor). Extensions for scale and rotational invariance are also discussed. Attempts were made to fully automate the process, replacing the human expert with equivalent image understanding routines. The methods used by the expert to select templates were criteria such as edge detail, contrast, and local histograms. These strategies were applied to automatically selected templates containing desired measurement points. Results and limitations are discussed.

Paper Details

Date Published: 1 August 1991
PDF: 12 pages
Proc. SPIE 1472, Image Understanding and the Man-Machine Interface III, (1 August 1991); doi: 10.1117/12.46481
Show Author Affiliations
Nandan G. Amladi, Univ. of Cincinnati (United States)
Michael K. Finegan, Univ. of Cincinnati (United States)
William G. Wee, Univ. of Cincinnati (United States)

Published in SPIE Proceedings Vol. 1472:
Image Understanding and the Man-Machine Interface III
Eamon B. Barrett; James J. Pearson, Editor(s)

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