Application of image processing techniques to the identification of phases in steel metallographic specimens

Abstract

Metallographic image processing focuses primarily on image segmentation, edge detection, and approximating grain size. This paper presents the results of applying a radial basis function neural network to the image texture data obtained from steel metallographic specimens to determine the feasibility of the automated recognition of steel phases.