Monitoring of mineral processing systems by using textural image analysis
In the last few decades, developments in machine vision technology have led to innovative approaches to the control and monitoring of mineral processing systems. Image representation plays an important role in the performance of the recognition systems used in these approaches, where the use of feat...
| Main Authors: | , , |
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| Format: | Journal Article |
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Elsevier
2013
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| Online Access: | http://hdl.handle.net/20.500.11937/40254 |
| _version_ | 1848755818447503360 |
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| author | Aldrich, Chris Kistner, M. Jemwa, G. |
| author_facet | Aldrich, Chris Kistner, M. Jemwa, G. |
| author_sort | Aldrich, Chris |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | In the last few decades, developments in machine vision technology have led to innovative approaches to the control and monitoring of mineral processing systems. Image representation plays an important role in the performance of the recognition systems used in these approaches, where the use of feature representations based on second-order statistics of the image pixels have predominated. However, these representations may not adequately capture or express the visual textural structure associated with the observed patterns in images. In this study, the use of texton and complex multiscale wavelet representations (steerable pyramids) that exploit higher-order statistical regularities, is investigated. These techniques are applied to two image data sets: industrial platinum group metals froth flotation, and coal particles on a conveyor belt. Compared to grey level co-occurrence matrix and classical wavelet representations, these are observed to improve performance when used as input in the pattern recognition phase. |
| first_indexed | 2025-11-14T09:02:21Z |
| format | Journal Article |
| id | curtin-20.500.11937-40254 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:02:21Z |
| publishDate | 2013 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-402542017-09-13T14:01:54Z Monitoring of mineral processing systems by using textural image analysis Aldrich, Chris Kistner, M. Jemwa, G. ore handling coal froth flotation process control In the last few decades, developments in machine vision technology have led to innovative approaches to the control and monitoring of mineral processing systems. Image representation plays an important role in the performance of the recognition systems used in these approaches, where the use of feature representations based on second-order statistics of the image pixels have predominated. However, these representations may not adequately capture or express the visual textural structure associated with the observed patterns in images. In this study, the use of texton and complex multiscale wavelet representations (steerable pyramids) that exploit higher-order statistical regularities, is investigated. These techniques are applied to two image data sets: industrial platinum group metals froth flotation, and coal particles on a conveyor belt. Compared to grey level co-occurrence matrix and classical wavelet representations, these are observed to improve performance when used as input in the pattern recognition phase. 2013 Journal Article http://hdl.handle.net/20.500.11937/40254 10.1016/j.mineng.2013.05.022 Elsevier restricted |
| spellingShingle | ore handling coal froth flotation process control Aldrich, Chris Kistner, M. Jemwa, G. Monitoring of mineral processing systems by using textural image analysis |
| title | Monitoring of mineral processing systems by using textural image analysis |
| title_full | Monitoring of mineral processing systems by using textural image analysis |
| title_fullStr | Monitoring of mineral processing systems by using textural image analysis |
| title_full_unstemmed | Monitoring of mineral processing systems by using textural image analysis |
| title_short | Monitoring of mineral processing systems by using textural image analysis |
| title_sort | monitoring of mineral processing systems by using textural image analysis |
| topic | ore handling coal froth flotation process control |
| url | http://hdl.handle.net/20.500.11937/40254 |