The CatchMeter is a computer vision system that can automatically measure the species and length of fish along with other extended information on colour and shape. Volume measurement of fish by laser scanning is also under development for integration into the system, offering the possibility of weight estimation.

Fish travel along an opaque blue, fast moving conveyor belt, through a computer vision system and can be presented in any position or orientation, against a complex background containing water, blood and other debris. The capacity of the system is 8,000–40,000 fish per hour with a conveyor belt speed of 1.5 m/s.

The CatchMeter is currently installed on the G.O. Sars and has been tested on three cruises to date and operated by non-expert users on a further two. In total more than 30,000 fish and 25 species have now been successfully analysed by the machine. For trained species the system has been shown to offer a classification accuracy of 98.6 % for 10 species and can be easily trained to recognise more as sufficient data becomes available. The minimum length of fish that can be measured is 50 mm, and since images can be stitched together the upper limit is >1.5 m. The length of fish is measured with an average standard deviation of 3 mm. The system has been developed by Scantrol, the University of Aberdeen, IMR and MATCON.

During the August 2006 Barents Sea cruise several improvements to the system have been implemented and tested:
· Higher resolution images (1392x1024).
· Software functionality and user friendliness improved.
· Opaque blue conveyor belt used and backlight system removed.
· Length measurement improved and tested thoroughly.
· Images of fish used to train system in previous cruises used to classify fish caught in current cruise.

Upcoming work includes integrating the CatchMeter system with the FishMeter system onboard, enabling the two to work together and store data in the same database. We see the CatchMeter as being the machine that will capture and store length and weight information of all fish, and then it will sort out the fish that need further analysis on a FishMeter. This sorting will be based on stratification rules set by the researchers.

Four papers have been written on the CatchMeter project so far. One is published, two are under review and another will be presented at the September 2006 ICES conference in Maastricht:

WHITE, D.J., SVELLINGEN, C. and STRACHAN, N.J.C., 2006. Automated Measurement of Species and Length of Fish by Computer Vision. Fisheries Research, 80, pp. 203-210.
WHITE, D.J., SVELLINGEN, C., STRACHAN, N.J.C., Submitted to journal 2006. Automated measurement of fish length using the CatchMeter computer vision system. Computers and electronics in agriculture.
WHITE, D.J., SVELLINGEN, C., STRACHAN, N.J.C., Submitted to journal 2006. Optimising colour variables for object recognition with application to fish species identification. Pattern Recognition Letters.
SVELLINGEN, C., TOTLAND, B., WHITE, D.J. and ØVREDAL, J.T. 2006. Automatic species recognition, length measurement and weight determination, using the CatchMeter computer vision system. ICES conference paper.

Cato Svellingen (Project leader, Scantrol, e-mail: cato at scantrol.no)
Darren White (PhD student, University of Aberdeen, e-mail: darren at scantrol.no)