Show simple item record

dc.contributor.authorRavanbakhsh, M.
dc.contributor.authorShortis, M.
dc.contributor.authorShaifat, F.
dc.contributor.authorMian, A.
dc.contributor.authorHarvey, Euan
dc.contributor.authorSeager, J.
dc.contributor.editorColin Arrowsmith, Chris Bellman, William Cartwright, Mark Shortis
dc.date.accessioned2017-01-30T12:50:08Z
dc.date.available2017-01-30T12:50:08Z
dc.date.created2015-01-22T20:00:46Z
dc.date.issued2014
dc.identifier.citationRavanbakhsh, M. and Shortis, M. and Shaifat, F. and Mian, A. and Harvey, E. and Seager, J. 2014. An Application of Shape-Based Level Sets to Fish Detection in Underwater Images, in C. Arrowsmith, C. Bellman, W. Cartwright, M. Shortis (ed), Proceedings of the Geospatial Science Research 3 Symposium, Dec 2 2014. Melbourne, Australia: CEUR Workshop Proceedings.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/25769
dc.description.abstract

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.

dc.publisherCEUR Workshop Proceedings
dc.relation.urihttp://ceur-ws.org/Vol-1307/paper6.pdf
dc.subjectunder-water image
dc.subjectfish detection
dc.subjectregistration
dc.subjectprior shape knowledge
dc.subjectlevel sets
dc.subjectimage segmentation
dc.titleAn Application of Shape-Based Level Sets to Fish Detection in Underwater Images
dc.typeConference Paper
dcterms.source.issn16130073
dcterms.source.titleProceedings of the Geospatial Science Research 3 Symposium
dcterms.source.seriesProceedings of the Geospatial Science Research 3 Symposium
dcterms.source.conferenceGeospatial Science Research 3 Symposium
dcterms.source.conference-start-dateDec 2 2014
dcterms.source.conferencelocationMelbourne, Australia
dcterms.source.placeGermany
curtin.note

Copyright © 2014 C. Arrowsmith, C. Bellman, W. Cartwright, M. Shortis

curtin.departmentDepartment of Environment and Agriculture
curtin.accessStatusFulltext not available


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record