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Proceedings Paper

Twin and scratch detection and removal in micrograph images of Inconel 718
Author(s): Gerhard Jakob; Alfred Rinnhofer; Horst Bischof; Wanda Benesova
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Paper Abstract

Grain size of forged nickel alloy is an important feature for the mechanical properties of the material. For fully automatic grain size evaluation in images of micrographs it is necessary to detect the boundaries of each grain. This grain boundary detection is influenced directly by artifacts like scratches and twins. Twins can be seen as parallel lines inside one grain, whereas a scratch can be identified as a sequence of collinear line segments that can be spread over the whole image. Both kinds of artifacts introduce artificial boundaries inside grains. To avoid wrong grain size evaluation, it is necessary to remove these artifacts prior to the size evaluation process. For the generation of boundary images various algorithms have been tested. The most stable results were achieved by grayscale reconstruction and a subsequent watershed segmentation. A modified line Hough transform with a third dimension in the Hough accumulator space, describing the distance of the parallel lines, is used to directly detect twins. Scratch detection is done by applying the standard line Hough transform followed by a rule based segment detection along the found Hough lines. The results of these operations give a detection rate of more than 90 percent for twins and more than 50 percent for scratches.

Paper Details

Date Published: 9 February 2006
PDF: 11 pages
Proc. SPIE 6070, Machine Vision Applications in Industrial Inspection XIV, 60700L (9 February 2006); doi: 10.1117/12.642635
Show Author Affiliations
Gerhard Jakob, Joanneum Research (Austria)
Alfred Rinnhofer, Joanneum Research (Austria)
Horst Bischof, Technical Univ. Graz (Austria)
Wanda Benesova, Joanneum Research (Austria)

Published in SPIE Proceedings Vol. 6070:
Machine Vision Applications in Industrial Inspection XIV
Fabrice Meriaudeau; Kurt S. Niel, Editor(s)

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