E3S Web Conf.
Volume 157, 2020Key Trends in Transportation Innovation (KTTI-2019)
|Number of page(s)||12|
|Published online||20 March 2020|
Waste disposal facilities monitoring based on high-resolution information features of space images
North Ossetia State Medical Academy, 40 Pushkinskaya., Vladikavkaz, 362019, Russia
2 Sochi State University, 94, Plastunskaya, Sochi, 354003, Russia
3 Russian-Armenian University, 123, Ovsepa Emina, Yerevan, 0051, Armenia
* Corresponding author: firstname.lastname@example.org
In the article there is represented and solved the problem of space images recognition for the presence of solid household and industrial waste without binarization. The methods of stochastic geometry and mathematical analysis are used. In the work there is proposed an algorithm based on a trace transformation using discrete orthogonal transformations (DOT) to minimize the attribute space and carry out studies on correctness by Tikhonov. For the implementation of the algorithm there are used elements of mathematical analysis, wavelet analysis, functional analysis, theory of discrete orthogonal transformations, methods for deciphering space images in the problem of stochastic scanning of space images based on the formation of a triplet attribute with minimization of attribute space using DOT. The development a trace matrices and the selection of informative features by stochastic geometry to find WDF from high-resolution space images are investigated from the point of view of DOT apparatus application. A study of the sustainability task was also performed. The proposed technique was tested using the example of space photographs with a WDF image. Conclusions are drawn on the use of the method proposed in this article for the task of automatic computer generation and selection of informative features for determining waste disposal facilities from high-resolution space images. It is proposed to use the Tikhonov regularization method to introduce stability in this task.
© The Authors, published by EDP Sciences, 2020
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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