Twin and Scratch Detection and Removal in Micrograph Images of Inconel TM 718
Publication from Digital
Electronic Imaging Science and Technology 2006, 15.-19.1.2006 in San Jose, USA. , 2006
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.
Keywords: grain size, twin boundary, scratch detection, superalloy, Hough transform, grayscale image reconstruction, watershed segmentation, intercept length