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Machine Vision and Applications

, Volume 13, Issue 1, pp 1–13 | Cite as

REFLICS: Real-time flow imaging and classification system

  • Sadahiro Iwamoto
  • David M. Checkley, Jr.
  • Mohan M. Trivedi
Original papers

Abstract.

An accurate analysis of a large dynamic system like our oceans requires spatially fine and temporally matched data collection methods. Current methods to estimate fish stock size from pelagic (marine) fish egg abundance by using ships to take point samples of fish eggs have large margins of error due to spatial and temporal undersampling. The real-time flow imaging and classification system (REFLICS) enhances fish egg sampling by obtaining continuous, accurate information on fish egg abundance as the ship cruises along in the area of interest. REFLICS images the dynamic flow with a progressive-scan area camera (60 frames/s) and a synchronized strobe in backlighting configuration. Digitization and processing occur on a dual-processor Pentium II PC and a pipeline-based image-processing board. REFLICS uses a segmentation algorithm to locate fish-egg-like objects in the image and then a classifier to determine fish egg, species, and development stage (age). We present an integrated system design of REFLICS and performance results. REFLICS can perform in real time (60 Hz), classify fish eggs with low false negative rates on real data collected from a cruise, and work in harsh conditions aboard ships at sea. REFLICS enables cost-effective, real-time assessment of pelagic fish eggs for research and management.

Key words: Real-time machine vision system – Pipeline-based image processing – Plankton – CUFES – Fish egg sampling – Survey 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Sadahiro Iwamoto
    • 1
  • David M. Checkley, Jr.
    • 2
  • Mohan M. Trivedi
    • 1
  1. 1.Computer Vision and Robotics Research Laboratory, Electrical and Computer Engineering Department, University of California, San Diego, 9500 Gilman Drive 0407, La Jolla, CA 92093-0407, USA; e-mail: {siwamoto,mtrivedi}@ucsd.edu; Tel.: +1 (858) 822-0002, Fax: +1 (858) 534-1004 US
  2. 2.Marine Life Research Group, Scripps Institution of Oceanography, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0218, USA; e-mail: dcheckley@ucsd.edu; Tel.: +1 (858) 534-4228, Fax: +1 (858) 822-0562 US

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