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All Journal International Journal of Electrical and Computer Engineering Indonesian Journal of Electrical Engineering and Computer Science
Saltanat Adikanova
Sarsen Amanzholov East Kazakhstan University
Computer Science & IT Electrical & Electronics Engineering

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Features of growth of agricultural crops and factors negatively affecting their growth Moldir Yessenova; Gulzira Abdikerimova; Zhanna B. Sadirmekova; Natalya Glazyrina; Saltanat Adikanova; Adilbek Tanirbergenov; Mukhamedrakhimov Karipola; Galiya Mukhamedrakhimova
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 1: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i1.pp625-632

Abstract

This article is about methods of analyzing aerial images. Images from Planet.com for crops in North Kazakhstan owned by the Center for Cereal Production and Research. A.I. Barayev. The main goal of the research work is to develop and implement algorithms that allow identifying and distinguishing factors in aerial photographs that adversely affect the growth of plants during the growing season. Spectral brightness coefficient (SBC), normalized difference vegetation index (NDVI), textural features, clustering, and integral transformations are used to solve the problem. Particular attention has been paid to the development of software tools for selecting features that describe textural differences to divide texture regions into subregions. That is weeds, and pests in aerial images. The application of a set of textural features and orthogonal transformations to the analysis of experimental data is explored to identify regions of potentially correlated features in the future. The analysis of the received data made it possible to determine the characteristics of changes in the reflective capacity of agricultural plants and weeds in certain stages of the growing season. The obtained information is of great importance for confirming the observations from space remote from the aerial images.
Application of informative textural Law’s masks methods for processing space images Moldir Yessenova; Gulzira Abdikerimova; Gulden Murzabekova; Kakabayev Nurbol; Natalya Glazyrina; Saltanat Adikanova; Nurgul Uzakkyzy; Zhanna B. Sadirmekova; Rozamgul Niyazova
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i4.pp4557-4566

Abstract

Image processing systems are currently used to solve many applied problems. The article is devoted to the identification of negative factors affecting the growth of grain in different periods of harvesting, using a program implemented in the MATLAB software environment, based on aerial photographs. The program is based on the Law’s textural mask method and successive clustering. This paper presents the algorithm of the program and shows the results of image processing by highlighting the uniformity of the image. To solve the problem, the spectral luminance coefficient (SBC), normalized difference vegetation index (NDVI), Law’s textural mask method, and clustering are used. This approach is general and has great potential for identifying objects and territories with different boundary properties on controlled aerial photographs using groups of images of the same surface taken at different vegetation periods. That is, the applicability of sets of Laws texture masks with original image enhancement for the analysis of experimental data on the identification of pest outbreaks is being investigated.
Co-Authors Adilbek Tanirbergenov Galiya Mukhamedrakhimova Gulden Murzabekova Gulzira Abdikerimova Kakabayev Nurbol Moldir Yessenova Mukhamedrakhimov Karipola Natalya Glazyrina Nurgul Uzakkyzy Rozamgul Niyazova Zhanna B. Sadirmekova Zhanna B. Sadirmekova