Fractal dimension (D or FD) is a measure of the complexity of self-similar data. One common method to quantify an image is to cover the picture with a grid of boxes, count the number of boxes in which the required feature appears, progressively increase the box size and count, then plot the detected feature measurement against box size. The slope of the line is D and the method works for images without self-similarity. The process is a feature of the NIH ImageJ freeware (other packages are available) image processing and analysis software. This technique reduces a processed image to a single real number, even where subjective assessment cannot perceive differences, which can then be used on one axis of a graph.The weave pattern of a woven reinforcement fabric, the permeability of reinforcement fabrics, the strength of fibre-reinforced composites, and reflections from a gel-coated surface have all been found to correlate to D. A rising issue is agglomeration of nanoparticles producing composites with reduced strength compared to uniformly distributed particles, which is normally discussed with qualitative judgement of microstructures, but the variation between images could easily be quantified by FD.

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School of Engineering, Computing and Mathematics


composites, fractal dimension, image