An Application of Shape-Based Level Sets to Fish Detection in Underwater Images

Underwater stereo-video technology systems are used widely for measurement of fish. However the effectiveness of the 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...

Full description

Bibliographic Details
Main Authors: Ravanbakhsh, M., Shortis, M., Shaifat, F., Mian, A., Harvey, Euan, Seager, J.
Other Authors: Colin Arrowsmith
Format: Conference Paper
Published: CEUR Workshop Proceedings 2014
Subjects:
Online Access:http://ceur-ws.org/Vol-1307/paper6.pdf
http://hdl.handle.net/20.500.11937/25769
_version_ 1848751800306368512
author Ravanbakhsh, M.
Shortis, M.
Shaifat, F.
Mian, A.
Harvey, Euan
Seager, J.
author2 Colin Arrowsmith
author_facet Colin Arrowsmith
Ravanbakhsh, M.
Shortis, M.
Shaifat, F.
Mian, A.
Harvey, Euan
Seager, J.
author_sort Ravanbakhsh, M.
building Curtin Institutional Repository
collection Online Access
description Underwater stereo-video technology systems are used widely for measurement of fish. However the effectiveness of the 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. Shape knowledge of fish is modelled by Principal Component Analysis (PCA). The Haar classifier is used for precise position 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 under-water 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 ofovercoming these limitations and capturing the fish outline at sub-pixel accuracy.
first_indexed 2025-11-14T07:58:29Z
format Conference Paper
id curtin-20.500.11937-25769
institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T07:58:29Z
publishDate 2014
publisher CEUR Workshop Proceedings
recordtype eprints
repository_type Digital Repository
spelling curtin-20.500.11937-257692023-02-27T07:34:30Z An Application of Shape-Based Level Sets to Fish Detection in Underwater Images Ravanbakhsh, M. Shortis, M. Shaifat, F. Mian, A. Harvey, Euan Seager, J. Colin Arrowsmith Chris Bellman William Cartwright Mark Shortis under-water image fish detection registration prior shape knowledge level sets image segmentation Underwater stereo-video technology systems are used widely for measurement of fish. However the effectiveness of the 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. Shape knowledge of fish is modelled by Principal Component Analysis (PCA). The Haar classifier is used for precise position 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 under-water 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 ofovercoming these limitations and capturing the fish outline at sub-pixel accuracy. 2014 Conference Paper http://hdl.handle.net/20.500.11937/25769 http://ceur-ws.org/Vol-1307/paper6.pdf CEUR Workshop Proceedings restricted
spellingShingle under-water image
fish detection
registration
prior shape knowledge
level sets
image segmentation
Ravanbakhsh, M.
Shortis, M.
Shaifat, F.
Mian, A.
Harvey, Euan
Seager, J.
An Application of Shape-Based Level Sets to Fish Detection in Underwater Images
title An Application of Shape-Based Level Sets to Fish Detection in Underwater Images
title_full An Application of Shape-Based Level Sets to Fish Detection in Underwater Images
title_fullStr An Application of Shape-Based Level Sets to Fish Detection in Underwater Images
title_full_unstemmed An Application of Shape-Based Level Sets to Fish Detection in Underwater Images
title_short An Application of Shape-Based Level Sets to Fish Detection in Underwater Images
title_sort application of shape-based level sets to fish detection in underwater images
topic under-water image
fish detection
registration
prior shape knowledge
level sets
image segmentation
url http://ceur-ws.org/Vol-1307/paper6.pdf
http://hdl.handle.net/20.500.11937/25769