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Detection of Fishes in Turbulent Waters Based on Image Analysis

  • Alvaro Rodriguez
  • Juan R. Rabuñal
  • Maria Bermudez
  • Jeronimo Puertas
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7931)

Abstract

This paper analyses the automatic fish segmentation problem in turbulent waters. To this end, a SOM neural network is used to detect fishes in images from an underwater camera system built in a vertical slot fishway, an hydraulic structure built in obstructions in rivers to allow the upstream migration of fishes.

This technique allows the study of real fish behavior and may help to understand biological variables and swimming limitations of the fish species in high speed environments.

This knowledge, may be used to replace traditional techniques such as direct observation or placement of sensors on the specimens, which are impractical or affect the fish behavior.

To test the proposed technique, a ground true dataset was designed with experts and a series of assays have been performed where the results obtained with the proposed technique were compared with different segmentation techniques.

Keywords

Fish-Detection Segmentation SOM Turbulent Water 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Alvaro Rodriguez
    • 1
  • Juan R. Rabuñal
    • 1
    • 2
  • Maria Bermudez
    • 3
  • Jeronimo Puertas
    • 3
  1. 1.Dept. of Information and Communications TechnologiesUniversity of A CoruñaA CoruñaSpain
  2. 2.Centre of Technological Innovation in Construction and Civil Engineering (CITEEC)University of A CoruñaA CoruñaSpain
  3. 3.Dept. of Hydraulic Engineering (ETSECCP)University of A CoruñaA CoruñaSpain

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