Flaw Detection Using a Priori Knowledge with Limited View Aperture System
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Begun in 1973, the Review of Progress in Quantitative Nondestructive Evaluation (QNDE) is the premier international NDE meeting designed to provide an interface between research and early engineering through the presentation of current ideas and results focused on facilitating a rapid transfer to engineering development.
This site provides free, public access to papers presented at the annual QNDE conference between 1983 and 1999, and abstracts for papers presented at the conference since 2001.
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Abstract
In CT imaging with limited view-angle data, the image of the object’s slice is usually distorted such that it is difficult to interpret the image. Usually in industrial applications. one deals with quality testing of products which are built from on an original blueprint or model. The objective of this paper is to use the knowledge about the model and try to establish whether there is any significant difference between the object under test and the model object. We will first formulate the problem as a deconvolution problem. Then we will use the CLEAN deconvolution algorithm to restore the image.