Processing and analysis of images of microstructure metals for determining the grain point
An algorithmic support for metallographic images preprocessing and analysis is presented. The software product implements metallographic methods for the grain size determination by comparison of rating scales, counting beans, calculation of grain boundaries intersections for equiaxed and elongated g...
| Main Authors: | , , |
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| Format: | Article |
| Language: | Russian |
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Educational institution «Belarusian State University of Informatics and Radioelectronics»
2021-07-01
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| Series: | Doklady Belorusskogo gosudarstvennogo universiteta informatiki i radioèlektroniki |
| Subjects: | |
| Online Access: | https://doklady.bsuir.by/jour/article/view/3110 |
| _version_ | 1797880953234784256 |
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| author | R. P. Bohush Y. R. Adamousky S. F. Denisenak |
| author_facet | R. P. Bohush Y. R. Adamousky S. F. Denisenak |
| author_sort | R. P. Bohush |
| collection | DOAJ |
| description | An algorithmic support for metallographic images preprocessing and analysis is presented. The software product implements metallographic methods for the grain size determination by comparison of rating scales, counting beans, calculation of grain boundaries intersections for equiaxed and elongated grains, measuring a chords length. Multiple digital images can be used as initial data. Pre-processing is used to remove noise, sharpen and improve contrast using Adaptive Contrast-Limiting Histogram Equalization (CLAHE). The next step is grain segmentation. A combination of distance transform and adaptive watershed binarization is used. Binary images filtration based on the operations of mathematical morphology is provided. Contour analysis is used to determine grain boundaries. The study’s results of the entire rating scales and on the real metallographic images are presented. High efficiency of an algorithmic support is confirmed by the experiments. The software implementation has the following main features: the ability to calibrate the actual grain size, automatic or manual image preprocessing, grain size analysis with saving the results as a report in jpg format. Batch processing provides the ability to download images for processing with the same type of algorithm. |
| first_indexed | 2024-04-10T03:11:20Z |
| format | Article |
| id | doaj.art-8e4b3d905f044133a708b3356d1f5ba8 |
| institution | Directory Open Access Journal |
| issn | 1729-7648 |
| language | Russian |
| last_indexed | 2024-04-10T03:11:20Z |
| publishDate | 2021-07-01 |
| publisher | Educational institution «Belarusian State University of Informatics and Radioelectronics» |
| record_format | Article |
| series | Doklady Belorusskogo gosudarstvennogo universiteta informatiki i radioèlektroniki |
| spelling | doaj.art-8e4b3d905f044133a708b3356d1f5ba82023-03-13T07:33:22ZrusEducational institution «Belarusian State University of Informatics and Radioelectronics»Doklady Belorusskogo gosudarstvennogo universiteta informatiki i radioèlektroniki1729-76482021-07-01194707910.35596/1729-7648-2012-19-4-70-791710Processing and analysis of images of microstructure metals for determining the grain pointR. P. Bohush0Y. R. Adamousky1S. F. Denisenak2Polotsk State UniversityPolotsk State UniversityPolotsk State UniversityAn algorithmic support for metallographic images preprocessing and analysis is presented. The software product implements metallographic methods for the grain size determination by comparison of rating scales, counting beans, calculation of grain boundaries intersections for equiaxed and elongated grains, measuring a chords length. Multiple digital images can be used as initial data. Pre-processing is used to remove noise, sharpen and improve contrast using Adaptive Contrast-Limiting Histogram Equalization (CLAHE). The next step is grain segmentation. A combination of distance transform and adaptive watershed binarization is used. Binary images filtration based on the operations of mathematical morphology is provided. Contour analysis is used to determine grain boundaries. The study’s results of the entire rating scales and on the real metallographic images are presented. High efficiency of an algorithmic support is confirmed by the experiments. The software implementation has the following main features: the ability to calibrate the actual grain size, automatic or manual image preprocessing, grain size analysis with saving the results as a report in jpg format. Batch processing provides the ability to download images for processing with the same type of algorithm.https://doklady.bsuir.by/jour/article/view/3110digital image processingparticle segmentationautomatic analysis of structures |
| spellingShingle | R. P. Bohush Y. R. Adamousky S. F. Denisenak Processing and analysis of images of microstructure metals for determining the grain point Doklady Belorusskogo gosudarstvennogo universiteta informatiki i radioèlektroniki digital image processing particle segmentation automatic analysis of structures |
| title | Processing and analysis of images of microstructure metals for determining the grain point |
| title_full | Processing and analysis of images of microstructure metals for determining the grain point |
| title_fullStr | Processing and analysis of images of microstructure metals for determining the grain point |
| title_full_unstemmed | Processing and analysis of images of microstructure metals for determining the grain point |
| title_short | Processing and analysis of images of microstructure metals for determining the grain point |
| title_sort | processing and analysis of images of microstructure metals for determining the grain point |
| topic | digital image processing particle segmentation automatic analysis of structures |
| url | https://doklady.bsuir.by/jour/article/view/3110 |
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