Physical Characterization of Materials by Grain Size Measurement Based Micrographic Images LSM-FCM Segmentation

Abstract

The aim of this work is to create an application that uses the ISO 643:2012 norm for the physical characterization of materials. This application, with its well adapted graphical interface offers the user a better processing of micrographic images, which allows an easy use; it will lead directly to reliable and reproducible results. In this paper, we are interested in determining the mean grain size in material using LSM (the level set method) based on FCM (fuzzy c-means clustering) to get the mean grains size of interest (types of surfaces) and to improve the precision of segmentation with a specified micrographic method. There are two steps in the proposed method. The first step involves using the fuzzy c-means algorithm to generate a clustered image. The second step is based on extracting the grains boundaries by using the appropriate class of the clustered image as an initial condition of the level set method. To achieve this objective, an application has been developed in the OpenCV library to make it easier for the expert to calculate grain sizes.