Application of Texture Features and Machine Learning Methods to Grain Segmentation in Rock Material Images
| Title: | Application of Texture Features and Machine Learning Methods to Grain Segmentation in Rock Material Images |
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| Authors: | Karolina Nurzynska, Sebastian Iwaszenko |
| Source: | Image Analysis and Stereology, Vol 39, Iss 2, Pp 73-90 (2020) |
| Publisher Information: | Slovenian Society for Stereology and Quantitative Image Analysis, 2020. |
| Publication Year: | 2020 |
| Collection: | LCC:Medicine (General) LCC:Mathematics |
| Subject Terms: | classification, grain sizes, object segmentation, texture features, Medicine (General), R5-920, Mathematics, QA1-939 |
| More Details: | The segmentation of rock grains on images depicting bulk rock materials is considered. The rocks’ material images are transformed by selected texture operators, to obtain a set of features describing them. The first order features, second-order features, run-length matrix, grey tone difference matrix, and Laws’ energies are used for this purpose. The features are classified using k-nearest neighbours, support vector machines, and artificial neural networks classifiers. The results show that the border of rocks grains can be determined with above 75% accuracy. The multi-texture approach was also investigated, leading to an increase in accuracy to over 79% for the early-fusion of features. Attempts were made to reduce feature space dimensionality by manually picking features as well as by the use of principal component analysis. The outcomes showed a significant decrease in accuracy. The obtained results have been visually compared with the ground truth. The compliance observed can be considered to be satisfactory. |
| Document Type: | article |
| File Description: | electronic resource |
| Language: | English |
| ISSN: | 1580-3139 1854-5165 |
| Relation: | https://www.ias-iss.org/ojs/IAS/article/view/2186; https://doaj.org/toc/1580-3139; https://doaj.org/toc/1854-5165 |
| DOI: | 10.5566/ias.2186 |
| Access URL: | https://doaj.org/article/ba116094b9da4e57b1f8a25525750f42 |
| Accession Number: | edsdoj.ba116094b9da4e57b1f8a25525750f42 |
| Database: | Directory of Open Access Journals |
| ISSN: | 15803139 18545165 |
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| DOI: | 10.5566/ias.2186 |
| Published in: | Image Analysis and Stereology |
| Language: | English |