Fractal Analysis to Determine Self-Similar Characteristics in the Microstructure of HSLA Steel

Abstract

A procedure based on statistical pattern recognition algorithm adopted for verifying the statistical self-similarity or fractal characteristics in microstructural images of metallic materials is reported in this article. The procedure is first applied on a synthetic image to show the degree of self-similarity in them and finally it has been applied on a microstructural image of steel. The results reported in this article have been used as a precursor for implementing fractal based quantification of microstructural images. Fractal based quantification is valid when the microstructure is homogeneous within certain length scales. Self-similar or self-affine characteristics of microstructures attribute such homogeneity in materials.