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All Journal International Journal of Electrical and Computer Engineering
Gulden Murzabekova
S. Seifullin Кazakh Agrotechnical University
Computer Science & IT Electrical & Electronics Engineering

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Journal : International Journal of Electrical and Computer Engineering

 1 
The effectiveness of methods and algorithms for detecting and isolating factors that negatively affect the growth of crops Moldir Yessenova; Gulzira Abdikerimova; Talgatbek Ayazbaev; Gulden Murzabekova; Aisulu Ismailova; Zhanar Beldeubayeva; Aliya Ainagulova; Ayagoz Mukhanova
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i2.pp1669-1679

Abstract

This article discusses a large number of textural features and integral transformations for the analysis of texture-type images. It also discusses the description and analysis of the features of applying existing methods for segmenting texture areas in images and determining the advantages and disadvantages of these methods and the problems that arise in the segmentation of texture areas in images. The purpose of the ongoing research is to use methods and determine the effectiveness of methods for the analysis of aerospace images, which are a combination of textural regions of natural origin and artificial objects. Currently, the automation of the processing of aerospace information, in particular images of the earth’s surface, remains an urgent task. The main goal is to develop models and methods for more efficient use of information technologies for the analysis of multispectral texture-type images in the developed algorithms. The article proposes a comprehensive approach to these issues, that is, the consideration of a large number of textural features by integral transformation to eventually create algorithms and programs applicable to solving a wide class of problems in agriculture. 
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 Aisulu Ismailova Aliya Ainagulova Ayagoz Mukhanova Gulzira Abdikerimova Kakabayev Nurbol Moldir Yessenova Natalya Glazyrina Nurgul Uzakkyzy Rozamgul Niyazova Saltanat Adikanova Talgatbek Ayazbaev Zhanar Beldeubayeva Zhanna B. Sadirmekova