Determing the average grain size of super-alloy micrographs
Publication from Digital
Benesova W. , Rinnhofer A., Jakob G.
IEEE - International Conference on Image Processing, ICIP 06 Atlanta, ,
This work presents a complex solution for determining the average
grain size and additional features in super-alloy (Inconeltrade 718)
micrographs. A crucial point of each automatic grain size measurement
system is a reliable segmentation of the grain boundaries using the
methods of image processing. This work introduces a novel method
for the marker image calculation, which is an essential part of the
grayscale image reconstruction. Unlike the methods of grayscale erosion
or image subtraction, our method uses the results of contour classification
for the goal-directed calculation of the marker image. The grayscale
image reconstruction therefore produces an excellent pre-processed
image with removed non-grain objects. In addition, the homogeneity
inside the grains increases without losing information about the
grain boundaries. When the automated grain size measurement using
the presented algorithm is compared to the manually evaluated average
grain size, we can confirm the acceptance of the proposed method
for application in metallurgical praxis.