Detection and classification of Lepeophterius salmonis (Krøyer, 1837) using Underwater Hyperspectral Imaging

Abstract Salmon louse, or sea lice, (Lepoptherius salmonis) represents practical, economical and fish welfare challenges for salmon farming (Hamre et al., 2013) and for the free-living stocks of salmon. There is an urgent need in the industry for a system that provides reliable numbers of louse on farmed salmon. Underwater hyperspectral imaging represents a potential new technique for louse counting in sea cages. In laboratory studies, the UHI technology could detect and classify pre-adults (pre-adult I and II), adult males and adult females (ovigerous) of sea lice based on the difference in their spectral characteristics. A model was built for detection of lice on the salmon and the UHI had a detection success ranging from 67 to 100 % with an average of 82%. A classification of the detected lice was performed for pre-adults, adult males and ovigerous lice and had a prediction accuracy of 85% when lice were divided into three groups (pre-adults, adult male and ovigerous lice) and 93% when lice were divided in two groups, ovigerous lice and all the other mobile lice (pre-adults and adult male). An automatic procedure for in situ measurements of louse infected salmon could deliver a data basis several times higher than the traditional counting system. The next generation of UHI louse detector should be developed with a higher spatial resolution to be able to detect also the sessile stages of lice. For succeeding with in situ classification of L. salmonis, correction algorithms to compensate for the impact of water between the UHI and lice need also to be developed.