Automated Fish Detection in Underwater Images Using Shape-Based level Sets
Underwater stereo-video systems are widely used for the measurement of fish. However, the effectiveness of stereo-video measurement has been limited because most operational systems still rely on a human operator. In this paper an automated approach for fish detection, using a shape-based level-sets...
| Main Authors: | , , , , , |
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| Format: | Journal Article |
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Wiley-Blackwell Publishing
2015
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| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.11937/32412 |
| _version_ | 1848753656325734400 |
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| author | Ravanbakhsh, M. Shortis, M. Shafait, F. Mian, A. Harvey, Euan Seager, J. |
| author_facet | Ravanbakhsh, M. Shortis, M. Shafait, F. Mian, A. Harvey, Euan Seager, J. |
| author_sort | Ravanbakhsh, M. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Underwater stereo-video systems are widely used for the measurement of fish. However, the effectiveness of stereo-video measurement has been limited because most operational systems still rely on a human operator. In this paper an automated approach for fish detection, using a shape-based level-sets framework, is presented. Knowledge of the shape of fish is modelled by principal component analysis (PCA). The Haar classifier is used for precise localisation of the fish head and snout in the image, which is vital information for close-proximity initialisation of the shape model. The approach has been tested on underwater images representing a variety of challenging situations typical of the underwater environment, such as background interference and poor contrast boundaries. The results obtained demonstrate that the approach is capable of overcoming these difficulties and capturing the fish outline to sub-pixel accuracy. |
| first_indexed | 2025-11-14T08:27:59Z |
| format | Journal Article |
| id | curtin-20.500.11937-32412 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T08:27:59Z |
| publishDate | 2015 |
| publisher | Wiley-Blackwell Publishing |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-324122017-09-13T15:24:21Z Automated Fish Detection in Underwater Images Using Shape-Based level Sets Ravanbakhsh, M. Shortis, M. Shafait, F. Mian, A. Harvey, Euan Seager, J. fish detection underwater image registration prior shape knowledge level sets image segmentation Underwater stereo-video systems are widely used for the measurement of fish. However, the effectiveness of stereo-video measurement has been limited because most operational systems still rely on a human operator. In this paper an automated approach for fish detection, using a shape-based level-sets framework, is presented. Knowledge of the shape of fish is modelled by principal component analysis (PCA). The Haar classifier is used for precise localisation of the fish head and snout in the image, which is vital information for close-proximity initialisation of the shape model. The approach has been tested on underwater images representing a variety of challenging situations typical of the underwater environment, such as background interference and poor contrast boundaries. The results obtained demonstrate that the approach is capable of overcoming these difficulties and capturing the fish outline to sub-pixel accuracy. 2015 Journal Article http://hdl.handle.net/20.500.11937/32412 10.1111/phor.12091 Wiley-Blackwell Publishing restricted |
| spellingShingle | fish detection underwater image registration prior shape knowledge level sets image segmentation Ravanbakhsh, M. Shortis, M. Shafait, F. Mian, A. Harvey, Euan Seager, J. Automated Fish Detection in Underwater Images Using Shape-Based level Sets |
| title | Automated Fish Detection in Underwater Images Using Shape-Based level Sets |
| title_full | Automated Fish Detection in Underwater Images Using Shape-Based level Sets |
| title_fullStr | Automated Fish Detection in Underwater Images Using Shape-Based level Sets |
| title_full_unstemmed | Automated Fish Detection in Underwater Images Using Shape-Based level Sets |
| title_short | Automated Fish Detection in Underwater Images Using Shape-Based level Sets |
| title_sort | automated fish detection in underwater images using shape-based level sets |
| topic | fish detection underwater image registration prior shape knowledge level sets image segmentation |
| url | http://hdl.handle.net/20.500.11937/32412 |