Fractal Analysis of Microstructural Images For Evaluation of HSLA Steel

Investigation of materials invariably requires usages of high resolution images of material structures for quantification of microstructural features, and subsequent development of correlations with the material properties. Often microstructural images of materials exhibit self similar structures or patterns formed due to network of grain boundaries, presence of precipitates, uneven surface elevations, etc. Microstructural images containing self similar fractal patterns at different length scales or resolutions remain unaffected by translations, rotations, projections and many other operations with regard to images. This makes the fractal analysis a useful technique for quantifying microstructural images by fractal dimension the non-integer dimensional exponent used for representing non-linear complex phenomena. This paper presents fractal analysis of a set of microstructural images of high strength low alloy (HSLA) steel at various aging conditions and reports that the variation of fractal dimensions identifies the morphological changes occurring in nano-scale due to copper precipitation.