Advertisement

System for Estimation of Pin Bone Positions in Pre-rigor Salmon

  • Jens T Thielemann
  • Trine Kirkhus
  • Tom Kavli
  • Henrik Schumann-Olsen
  • Oddmund Haugland
  • Harry Westavik
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4678)

Abstract

Current systems for automatic processing of salmon are not able to remove all bones from freshly slaughtered salmon. This is because some of the bones are attached to the flesh by tendons, and the fillet is damaged or the bones broken if the bones are pulled out. This paper describes a camera based system for determining the tendon positions in the tissue, so that the tendon can be cut with a knife and the bones removed. The location of the tendons deep in the tissue is estimated based on the position of a texture pattern on the fillet surface. Algorithms for locating this line-looking pattern, in the presence of several other similar-looking lines and significant other texture are described. The algorithm uses a model of the pattern’s location to achieve precision and speed, followed by a RANSAC/MLESAC inspired line fitting procedure. Close to the neck the pattern is barely visible; this is handled through a greedy search algorithm. We achieve a precision better than 3 mm for 78% of the fish using maximum 2 seconds processing time.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Braeger, H., Moller, W.: Apparatus for gaining pinbone-free fillets of fish, US Patent 4748723 (1987)Google Scholar
  2. 2.
    Davis, E.R.: Machine Vision: Theory, Algorithms, Practicalities, pp. 269–271. Academic Press, London (1990)Google Scholar
  3. 3.
    Fischler, M.A., Bolles, R.C.: Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography. Comm. of the ACM 24, 381–395 (1981)CrossRefGoogle Scholar
  4. 4.
    Haugland, O., Voll, T.: Mechanism and apparatus to ease extraction of pin bones, Norwegian patent 319441.Google Scholar
  5. 5.
    Kryvi, H., Totland, G.: Fiskeanatomi (Fish anatomy), Høyskoleforlaget AS (1997), ISBN 82-7634-056-3-5Google Scholar
  6. 6.
    Pratt, W.K.: Digital Image Processing, 2nd edn., pp. 553–555. John Wiley & Sons Inc., NY (1991)zbMATHGoogle Scholar
  7. 7.
    Torr, P., Zissermann, A.: MLESAC: a new robust estimator with application to estimating image geometry. Computer Vision and Image Understanding 78(1), 138–156Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Jens T Thielemann
    • 1
  • Trine Kirkhus
    • 1
  • Tom Kavli
    • 1
  • Henrik Schumann-Olsen
    • 1
  • Oddmund Haugland
    • 2
  • Harry Westavik
    • 3
  1. 1.SINTEF, PB 124 Blindern, N-0314 OsloNorway
  2. 2.Trio Fish Processing Machinery AS, P.O. Box 38, Forus, NO-4064 StavangerNorway
  3. 3.SINTEF Fisheries and Aquaculture AS, N-7465 TrondheimNorway

Personalised recommendations