J. R. MATHIASSEN(a), S. JANSSON(b), E. VELIYULIN, T. NJAA, M. LØNSETH, M. BONDØ, S. O. ØSTVIK, J. RISDAL and A. SKAVHAUG
SINTEF Fisheries and Aquaculture AS, N-7465 Trondheim, Norway Fax: + 47 932 70 701, E-mail: John.R.Mathiassen@sintef.no
SINTEF Fisheries and Aquaculture AS, N-7465 Trondheim, Norway Fax: + 47 932 70 701, E-mail: Stig.Jansson@sintef.no
ABSTRACT Despite good availability of pelagic fish, the Norwegian pelagic enterprises are suffering from both overcapacity and low margins. The reasons for this situation are diverse, e.g. high labor costs, trade barriers and long distances to the markets. In order to cope with competition from other countries, the most important issue is to lower labor costs while maintaining quality. In this article we describe a proof-of-concept prototype of an automated system for weight and quality grading of pelagic fish using a multi-modal machine vision system combined with robotized sorting. This system can potentially replace the majority of the manual operators needed today.
For some years now, there have been both an increased demand for, and value attributed to higher quality of mackerel and herring. Typical demands include more precise weight class distribution and less damaged fish. This creates incentives to find more accurate methods for weight and quality grading. The common way of performing weight grading today is to make use of V-belts or rotating rollers that separate the fish into 4-5 weight classes. The accuracy of these methods depends on the body index as well as the condition of the fish texture. These are factors that are directly influenced by how the catching and handling has been carried through, and even with a skilled vessel crew there will be variations in the catch quality. The quality grading today is predominantly done by one to four operators. These grading tasks normally consist of removing... [continues]
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