| Issue |
E3S Web of Conf.
Volume 389, 2023
Ural Environmental Science Forum “Sustainable Development of Industrial Region” (UESF-2023)
|
|
|---|---|---|
| Article Number | 07008 | |
| Number of page(s) | 12 | |
| Section | IT in Environmental Science | |
| DOI | https://doi.org/10.1051/e3sconf/202338907008 | |
| Published online | 31 May 2023 | |
Method for calculating the heterogeneity of the linear dimensions of the EIT image
1 Platov South-Russian State Polytechnic University (NPI), 132, str. Enlightenment, 346428, Novocherkassk, Russia
2 Le Quy Don Technical University, 463 Hoàng Quốc Việt, P, 129810, Nam Từ Liêm, Hà Nội, Viet Nam
* Corresponding author: mari.mak787@yandex.ru
The paper proposes a method for calculating the heterogeneity of the linear dimensions of the EIT image. The essence of the method is to identify the region of inhomogeneity Gn by the method of binarization and segmentation and determine its geometric dimensions. The ROI represents a matrix, each element of which is the color value of a particular pixel p. The reconstructed image is being processed. The binarization algorithm processes and determines each element of the matrix, bringing it to a binary form. Next, a w × h matrix is formed and the image is divided into sets p, where, according to the selection criterion Gn, the segmentation procedure is performed using the two-pass ABC-mask method. At the last stage, the geometric dimensions of the inhomogeneity are determined. The results of the analysis of the reconstructed image are presented, the image of the inhomogeneity Gn filtered as a result of binarization and segmentation operations, as well as its geometric parameters are obtained. The operation of the method on computer models for inhomogeneities has been verified. The proposed method allows you to get a clearer and more accurate visualization of the internal structures of the object under study, reduce measurement errors and incorrect solution of the inverse problem.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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