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.
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