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A method and software solution for classifying clast roundness based on the radon transform
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DOI：10.1016/j.cageo.2020.104451.png)
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Abstract
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In this paper, an algorithm for clast roundness classification based on the Radon transform is presented. The degree of roundness is determined by processing the sinogram of the clast image. The algorithm consists in applying two low-pass filters to the sinogram, obtaining the inverse Radon transform and comparing the filtered images with the original image. For rounded particles, the difference between the original image and either of the filtered images will be small. For angular clasts, the difference will be greater than for rounded clasts, due to the presence of high-frequency components. In the comparison process, each of the two filtered images are subtracted from the original image to yield two difference images. Since the data are binary, these two images present topologically unconnected regions that correspond to the particle's edges. The percentage of nonoverlapping area between the original and the difference images, and the number of regions are used to classify the morphology of the clast. The results have been validated using a comparison chart designed for visual roundness estimation. The comparison chart, consisting of five roundness classes, was proposed by Russell, Taylor and, Pettijohn (Willer, 1967). Two cutoff frequencies, one to classify well-rounded, rounded and sub-rounded clasts and another for angular and sub-angular classes, were used. The proposed algorithm correctly classifies the roundness classes of the visual graph. The results provided by the algorithm were compared with the classification performed by a group of experts. The algorithm assigned 92% of the clasts to the same classes as the human experts. We also propose Gaussian models, which are useful to classify the particles into the five classes. We have developed a user-friendly software to carry out the roundness classification algorithm. This software was developed on the MATLAB platform and can be freely downloaded from the public repository.
Keywords:
Clast morphology
Roundness
Radon transform
Texture analysis
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