Identification of factors that negatively affect the growth of agricultural crops by methods of orthogonal transformations

Authors

DOI:

https://doi.org/10.15587/1729-4061.2022.257431

Keywords:

image processing, aerospace images, NDVI, SBC, orthogonal transformations, conceptual model

Abstract

This paper focuses on aerospace image analysis methods. Aerospace images are considered for the study of agricultural crops of northern Kazakhstan belonging to the A. I. Barayev Research and Production Center for Grain Farming. The main goal of the research is the development and implementation of algorithms that make it possible to detect and highlight on aerospace images the factors that negatively affect the growth of crops over the growing seasons. To resolve the problem, the spectral brightness coefficient (SBC), NDVI, clustering, orthogonal transformations are used. Special attention was paid to the development of software tools for selecting characteristics that describe texture differences to segment texture regions into sub-regions. That is, the issue of the applicability of sets of textural features and orthogonal transformations for the analysis of experimental data to identify characteristic areas on aerospace images that can be associated with weeds, pests, etc. in the future was investigated. The questions of signal image processing remain the focus of attention of different specialists. The images act both as a result and as a research object in physics, astronautics, meteorology, forensic medicine and many other areas of science and technology. Furthermore, image processing systems are currently being used to resolve many applied problems.

A program has been implemented in the MATLAB environment that allows performing spectral transformations of six types: 1) cosine; 2) Hadamard of order 2n; 3) Hadamard of order n=p+1, p≡3 (mod4); 4) Haar; 5) slant; 6) Daubechies 4.

Analysis of the data obtained revealed the features of changes in the reflectivity of cultivated crops and weeds in certain periods of the growing season. The data obtained are of great importance for the validation of remote space observations using aerospace images

Author Biographies

Moldir Yessenova, L. N. Gumilyov Eurasian National University

Doctoral Student

Department of Information Systems

Gulzira Abdikerimova, L. N. Gumilyov Eurasian National University

PhD

Department of Information Systems

Aknur Adilova, M. Kh. Dulaty Taraz Regional University

Teacher

Department of Information Systems

Akbota Yerzhanova, S. Seifullin Kazakh Agrotechnical University

Teacher

Department of Technological Machines and Equipment

Nurbol Kakabayev, Ualikhanov University

Doktor PhD, Аssociate Professor

Department of Engineering Technology and Transport

Talgatbek Ayazbaev, International Taraz Innovative Institute

Candidate of Physiko-Mathematical Sciences, Associate Professor

Department of Information and Communication Technologies

Zeinigul Sattybaeva, Ualikhanov University

Аssociate Professor

Department of Agriculture of Bioresources

Tleugaisha Ospanova, L. N. Gumilyov Eurasian National University

Candidate of Technical Sciences

Department of Information Systems

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Published

2022-06-30

How to Cite

Yessenova, M., Abdikerimova, G., Adilova, A., Yerzhanova, A., Kakabayev, N., Ayazbaev, T., Sattybaeva, Z., & Ospanova, T. (2022). Identification of factors that negatively affect the growth of agricultural crops by methods of orthogonal transformations . Eastern-European Journal of Enterprise Technologies, 3(2 (117), 39–47. https://doi.org/10.15587/1729-4061.2022.257431

Issue

Vol. 3 No. 2 (117) (2022): Information technology. Industry control systems

Section

Information technology

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Copyright (c) 2022 Moldir Yessenova, Gulzira Abdikerimova, Aknur Adilova, Akbota Yerzhanova, Nurbol Kakabayev, Talgatbek Ayazbaev, Zeinigul Sattybaeva, Tleugaisha Ospanova

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