Automatic ore image segmentation using mean shift and watershed transform
In this paper, we present a novel method for segmenting ore images specifically for estimating the size distribution of ore material on conveyer belt. The segmentation system uses the mean shift and watershed algorithm. The mean shift algorithm is used to identify pixel clusters of particular modes...
| Main Authors: | , |
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| Format: | Conference Paper |
| Published: |
2011
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| Online Access: | http://hdl.handle.net/20.500.11937/20170 |
| _version_ | 1848750233053298688 |
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| author | Amankwah, A. Aldrich, Chris |
| author_facet | Amankwah, A. Aldrich, Chris |
| author_sort | Amankwah, A. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | In this paper, we present a novel method for segmenting ore images specifically for estimating the size distribution of ore material on conveyer belt. The segmentation system uses the mean shift and watershed algorithm. The mean shift algorithm is used to identify pixel clusters of particular modes of the probability density function of the image data. The pixel clusters are then used to generate markers for the watershed transform and shadow areas in ore image. Experimental results show that the proposed algorithm is not only faster than the standard methods but also more robust. |
| first_indexed | 2025-11-14T07:33:34Z |
| format | Conference Paper |
| id | curtin-20.500.11937-20170 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T07:33:34Z |
| publishDate | 2011 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-201702017-09-13T13:48:57Z Automatic ore image segmentation using mean shift and watershed transform Amankwah, A. Aldrich, Chris In this paper, we present a novel method for segmenting ore images specifically for estimating the size distribution of ore material on conveyer belt. The segmentation system uses the mean shift and watershed algorithm. The mean shift algorithm is used to identify pixel clusters of particular modes of the probability density function of the image data. The pixel clusters are then used to generate markers for the watershed transform and shadow areas in ore image. Experimental results show that the proposed algorithm is not only faster than the standard methods but also more robust. 2011 Conference Paper http://hdl.handle.net/20.500.11937/20170 10.1109/RADIOELEK.2011.5936391 restricted |
| spellingShingle | Amankwah, A. Aldrich, Chris Automatic ore image segmentation using mean shift and watershed transform |
| title | Automatic ore image segmentation using mean shift and watershed transform |
| title_full | Automatic ore image segmentation using mean shift and watershed transform |
| title_fullStr | Automatic ore image segmentation using mean shift and watershed transform |
| title_full_unstemmed | Automatic ore image segmentation using mean shift and watershed transform |
| title_short | Automatic ore image segmentation using mean shift and watershed transform |
| title_sort | automatic ore image segmentation using mean shift and watershed transform |
| url | http://hdl.handle.net/20.500.11937/20170 |