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Fish species recognition using computer vision and a neural network
Storbeck, F.; Daan, B. (2001). Fish species recognition using computer vision and a neural network. Fish. Res. 51: 11-15
In: Fisheries Research. Elsevier: Amsterdam. ISSN 0165-7836, more
Peer reviewed article  

Available in  Authors 

Keywords
    Computer vision; Computer vision; Computer vision; Pattern recognition; Process control; Process control; Marine

Authors  Top 
  • Storbeck, F.
  • Daan, B.

Abstract
    A system is described to recognize fish species by computer vision and a neural network program. The vision system measures a number of features of fish as seen by a camera perpendicular to a conveyor belt. The features used here are the widths and heights at various locations along the fish. First the measured values are used as input values to a neural network, together with the information on the species. The network is trained to recognize the species from these input data. To decrease the time to train the network, a learning rate, a momentum factor and the elimination of non-contributing connections and nodes were introduced. Testing of the network showed that more than 95% of the fish could be classified correctly.

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