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An automatic image-based system for detecting wild and stocked fish

Myrum, Espen; Nørstebø, Simen Andre; George, Sony; Pedersen, Marius; Museth, Jon
Journal article, Peer reviewed
Published version
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URI
http://hdl.handle.net/11250/2639552
Date
2019
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  • Institutt for datateknologi og informatikk [3771]
  • Publikasjoner fra CRIStin - NTNU [19694]
Original version
NIK: Norsk Informatikkonferanse. 2019, .  
Abstract
Fish stocking is the method of raising fish in a hatchery and releasing them into a river or lake to sustain or increase an existing population or to create a population. This has been practised in many countries, including Norway. Before the fish are released, the adipose fin is commonly removed in order to identify that it is a stocked fish. Cameras have been mounted in several Norwegian rivers in order to monitor fish populations. Classification of fish from these cameras is today a manual task carried out by people. In this paper we propose an automatic classification method to separate wild fish from stocked fish using machine learning. Experiments on an image set of trouts (Salmo Trutta) show a very high accuracy of the proposed method.
Publisher
Bibsys Open Journal Systems
Journal
NIK: Norsk Informatikkonferanse

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