Contour Matching for Fish Species Recognition and Migration Monitoring

  • Dah-Jye Lee
  • James K. Archibald
  • Robert B. Schoenberger
  • Aaron W. Dennis
  • Dennis K. Shiozawa
Part of the Studies in Computational Intelligence book series (SCI, volume 122)

Summary

A variety of matching and classification techniques have been employed in applications requiring pattern recognition. In this chapter we introduce a simple and accurate real-time contour matching technique specifically for applications involving fish species recognition and migration monitoring. We describe FishID, a prototype vision system that employs a software implementation of our newly developed contour matching algorithms. We discuss the challenges involved in the design of this system, both hardware and software, and we present results from a field test of the system at Prosser Dam in Prosser, Washington. In tests with up to four distinct species, the algorithm correctly determines the species with greater than 90 percent accuracy.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Dah-Jye Lee
    • 1
  • James K. Archibald
    • 1
  • Robert B. Schoenberger
    • 2
  • Aaron W. Dennis
    • 1
  • Dennis K. Shiozawa
    • 3
  1. 1.Department of Electrical and Computer EngineeringBrigham Young UniversityProvoUSA
  2. 2.Symmetron, LLC a div. of ManTech International Corp.FairfaxUSA
  3. 3.Department of BiologyBrigham Young UniversityProvoUSA

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