Репозиторий Dspace

SEGMENTATION OF AEROSPACE IMAGES BY A NON-STANDARD APPROACH USING INFORMATIVE TEXTURAL FEATURES

Показать сокращенную информацию

dc.contributor.author Yerzhanova, Akbota
dc.contributor.author Abdikerimova, Gulzira
dc.contributor.author Alimova, Zhanar
dc.contributor.author Slanbekova, Assylzat
dc.contributor.author Tungatarova, Aigul
dc.contributor.author Muratkhan, Raikhan
dc.contributor.author Borankulova, Gaukhar
dc.contributor.author Zhunussova, Gulzat
dc.date.accessioned 2024-09-23T10:13:04Z
dc.date.available 2024-09-23T10:13:04Z
dc.date.issued 2022
dc.identifier.citation Yerzhanova, A., Abdikerimova, G., Alimova, Z., Slanbekova, A., Tungatarova, A., Muratkhan, R., Borankulova, G., Zhunussova, G. (2022). Segmentation of aerospace images by a non-standard approach using informative textural features. Eastern-European Journal of Enterprise Technologies, 1 (2 (115)), 39–49. doi: https://doi.org/10.15587/1729-4061.2022.253188 ru
dc.identifier.issn 1729-3774
dc.identifier.uri https://doi.org/10.15587/1729-4061.2022.253188
dc.identifier.uri http://rep.enu.kz/handle/enu/16833
dc.description.abstract The article presents an analysis of a non-standard approach to the segmentation of textural areas in aerospace images. The question of the applicability of sets of textural features for the analysis of experimental data is being investigated to identify characteristic areas on aerospace images that in the future it will be possible to identify types of crops, weeds, diseases, and pests. The selection of suitable algorithms was carried out and appropriate software tools were created on Matlab 2021a and in the software package for statistical analysis Statistica 12. The main way to extract information is to decrypt images, which are the main carrier of information about the underlying surface. The main tasks of texture area analysis include selection and formation of features describing textural differences; selection and segmentation of textural areas; classification of textural areas; identification of an object by texture. To solve the tasks, spectral brightness coefficient (SBC), Normalized Difference Vegetation Index (NDVI), textural features of various crops and weeds. Much attention will be paid to the development of software tools that allow the selection of features describing textural differences for the segmentation of textural areas into subdomains. That is the question of the applicability of sets of textural features and other parameters for the analysis of experimental data to identify types of soils and soils, vegetation types, humidity, crop damage in aerospace images will be resolved. This approach is universal and has great potential for identifying objects using image clustering. To identify the boundaries of areas with different properties of the image under study, images of the same surface area taken at different times are considered. ru
dc.language.iso en ru
dc.publisher Eastern-European Journal of Enterprise Technologies ru
dc.relation.ispartofseries Volume 1, Issue 2-115;Pages 39 - 49
dc.subject Agricultural crops ru
dc.subject Clustering ru
dc.subject Image processing ru
dc.subject Ndvi ru
dc.subject Pests ru
dc.subject Satellite images ru
dc.subject Sbc ru
dc.subject Textural features ru
dc.subject Weeds ru
dc.title SEGMENTATION OF AEROSPACE IMAGES BY A NON-STANDARD APPROACH USING INFORMATIVE TEXTURAL FEATURES ru
dc.type Article ru


Файлы в этом документе

Данный элемент включен в следующие коллекции

Показать сокращенную информацию

Поиск в DSpace


Просмотр

Моя учетная запись