Determining the Average Grain Size of Super-Alloy Micrographs

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