Paper
31 January 2020 Segmentation criteria in the problem of porosity determination based on CT scans
Author Affiliations +
Proceedings Volume 11433, Twelfth International Conference on Machine Vision (ICMV 2019); 114331E (2020) https://doi.org/10.1117/12.2558081
Event: Twelfth International Conference on Machine Vision, 2019, Amsterdam, Netherlands
Abstract
Porous materials are widely used in different applications, in particular they are used to create various filters. Their quality depends on parameters that characterize the internal structure such as porosity, permeability and so on. Сomputed tomography (CT) allows one to see the internal structure of a porous object without destroying it. The result of tomography is a gray image. To evaluate the desired parameters, the image should be segmented. Traditional intensity threshold approaches did not reliably produce correct results due to limitations with CT images quality. Errors in the evaluation of characteristics of porous materials based on segmented images can lead to the incorrect estimation of their quality and consequently to the impossibility of exploitation, financial losses and even to accidents. It is difficult to perform correctly segmentation due to the strong difference in voxel intensities of the reconstructed object and the presence of noise. Image filtering as a preprocessing procedure is used to improve the quality of segmentation. Nevertheless, there is a problem of choosing an optimal filter. In this work, a method for selecting an optimal filter based on attributive indicator of porous objects (should be free from "levitating stones" inside of pores) is proposed. In this paper, we use real data where beam hardening artifacts are removed, which allows us to focus on the noise reduction process.
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
V. Kokhan, M. Grigoriev, A. Buzmakov, V. Uvarov, A. Ingacheva, and E. Shvets "Segmentation criteria in the problem of porosity determination based on CT scans", Proc. SPIE 11433, Twelfth International Conference on Machine Vision (ICMV 2019), 114331E (31 January 2020); https://doi.org/10.1117/12.2558081
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KEYWORDS
Digital filtering

Image filtering

Image segmentation

Anisotropic filtering

Anisotropic diffusion

Diffusion

Image processing

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