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ICES Journal of Marine Science: Journal du Conseil Advance Access originally published online on March 11, 2008
ICES Journal of Marine Science: Journal du Conseil 2008 65(4):636-644; doi:10.1093/icesjms/fsn029
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© 2008 US Government and the NOAA Fisheries, Department of Commerce. For Permissions, please email: journals.permissions@oxfordjournals.org

Automated tracking of fish in trawls using the DIDSON (Dual frequency IDentification SONar)

Nils Olav Handegard1 and Kresimir Williams2

1 Institute for Marine Research, PO Box 1870 Nordnes, 5817 Bergen, Norway
2 Alaska Fisheries Science Center, National Marine Fisheries Service, 7600 Sand Point Way NE, Seattle, WA 98115, USA

Correspondence to N. O. Handegard: tel: +47 55 236803; fax: +47 55 236830; e-mail: nils.olav.handegard{at}imr.no

Handegard, N. O., and Williams, K. 2008. Automated tracking of fish in trawls using the DIDSON (Dual frequency IDentification SONar). – ICES Journal of Marine Science. 65: 636–644.

An application for the automated tracking of dual-frequency, identification sonar (DIDSON) data was developed and tested on fish observations taken in midwater trawls. The process incorporates target detection, multiple target tracking, and the extraction of behaviour information such as target speed and direction from the track data. The automatic tracker was evaluated using three test datasets with different target sizes, observation ranges, and densities. The targets in the datasets were tracked manually and with the automated tracker, using the manual-tracking results as the standard for estimating the performance of the automated tracking process. In the first and third dataset, where the targets were smaller and less dense, the automated tracking performed well, correctly identifying 74% and 57% of targets, respectively, and associating targets into tracks with <10% error compared with the manually tracked data. In the second dataset, where targets were dense and appeared large owing to the shorter observation range, 45% of targets were correctly identified, and the track error rate was 21%. Target speed and direction, derived from the tracking data, agreed well between the manual and automatic methods for all three test cases. Automated tracking represents a useful technique for processing DIDSON data, and a valuable alternative to time-consuming, manual data-processing, when used in appropriate conditions.

Keywords: DIDSON, multiple-target tracking, trawl-behaviour observation

Received 13 June 2007; accepted 14 January 2008; advance access publication 11 March 2008.


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