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     Target fish species are recorded to help properly manage, regulate, and protect migratory fisheries by accurately monitoring numbers, size, and species of fish at specific fish passages during migratory seasons. After capturing images of different fish species, the contour of each image is extracted to form a closed curve for shape analysis. A new shape analysis algorithm was developed for removing edge noise and redundant data points such as short straight lines. A curvature function analysis is used to locate critical landmark points. The fish contour segments of interest is then extracted based on these landmark points for species classification. By comparing individual contour segments to the curves in the database, patterns can be accurately matched to identify the fish species.

 Project Sponsors:

 Agris-Schoen Vision Systems, Inc (2003~2006)

 USDA SBIR Grant # 2003-33610-13132 (May 2003 ~ Nov 2003)

 USDA SBIR Grant # 2004-33610-14804 (Sep 2004 ~ Sep 2006)


 Mr. Robert Schoenberger, Agris-Schoen Vision Systems, Inc.
 Dr. Dennis Shiozawa, Brigham Young University

 Mr. Robert Lane, Virginia Tech
 Dr. Eamonn Keogh, University of California - Riverside

 Graduate Students:

 Aaron Dennis

  1. X. Xi, K. Ueno, E. Keogh, and D.J. Lee, “Converting Non-parametric Distance-Based Classification to Anytime
    Algorithms,” special issue on “Non-parametric Distance-based Classification Techniques and their Applications” of
    Pattern Analysis and Applications, vol. 11/3-4, p. 321-336, September 2008.
  2. D.J. Lee, J.K. Archibald, R.B. Schoenberger, A.W. Dennis, and D.K. Shiozawa, "Contour Matching for Fish Species
    Recognition and Migration Monitoring”, Applications of Computational Intelligence in Biology: Current Trends and
    Open Problems, Springer-Verlag, ISBN: 978-3-540-78533-0, vol. 122, p. 183-207, June 2008.

  3. K. Ueno, X. Xi, E. Keogh, and D.J. Lee, “Anytime Classification Using the Nearest Neighbor Algorithm with Applications to Stream Mining”, The 2006 IEEE International Conference on Data Mining, Hong Kong, December 18-22, 2006.

  4. D. J. Lee, S. Redd, R.B. Schoenberger, X. Xu, and P. Zhan, “An Automated Fish Species Classification and Migration Monitoring System”, Proceedings of The 29th Annual Conference of the IEEE Industrial Electronics Society, p. 1080-1085, Roanoke, Virginia, USA, November 2-6, 2003.

  5. D.J. Lee, R.B. Schoenberger, D.K. Shiozawa, X. Xu, and P. Zhan, “Contour Matching for a Fish Recognition and Migration Monitoring System”, SPIE Optics East, Two and Three-Dimensional Vision Systems for Inspection, Control, and Metrology II, vol. 5606-05, p. 37-48, Philadelphia, PA, USA, October 25-28, 2004.

  6. D.J. Lee, P. Zhan, D.K. Shiozawa, and R.B. Schoenberger, “An Automated Fish Recognition and Migration Monitoring System for Biology Research”, The 2004 Annual Meeting of the Western Division of the American Fisheries Society, Salt Lake City, UT, USA, March 1-4, 2004.

  7. C. Strout, D.K. Shiozawa, and D.J Lee, “Computerized Fish Imaging and Population Count Analysis”, The 2004 Annual Meeting of the Western Division of the American Fisheries Society, Salt Lake City, UT, USA, March 1-4, 2004.

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