Determing the average grain size of super-alloy micrographs

Publikation aus 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.