Novel system for semiautomatic image segmentation of arctic charr

We propose a practical schema for semiautomatic segmentation of images of Arctic charr. The goal is to separate differently colored parts of the fish, especially red abdominal areas from the other parts. The novelty and importance of the proposed system are in the reconstruction of a working schema rather than its components. The system is important to fisheries since the coloration of fish is connected to the genetic quality and is often used to evaluate the health status of the fish. Quantitative analysis of this kind of information gives follow-up data and a more realistic view of fish stock than the basic visual evaluation. The schema takes consideration of economical limitations of an ordinary fishery and educational aspects of personnel. The results are evaluated visually by the experts and against a neural network solution.

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