Automatic In Situ Identification of Plankton

Authors:
Matthew B. Blaschko;Gary Holness;Marwan A. Mattar;Dimitri Lisin;Paul E. Utgoff;Allen R. Hanson;Howard Schultz;Edward M. Riseman;Michael E. Sieracki;William M. Balch;Ben Tupper
Affiliations:
University of Massachusetts Amherst, MA;University of Massachusetts Amherst, MA;University of Massachusetts Amherst, MA;University of Massachusetts Amherst, MA;University of Massachusetts Amherst, MA;University of Massachusetts Amherst, MA;University of Massachusetts Amherst, MA;University of Massachusetts Amherst, MA;Bigelow Laboratory for Ocean Sciences, West Boothbay Harbor, ME;Bigelow Laboratory for Ocean Sciences, West Boothbay Harbor, ME;Bigelow Laboratory for Ocean Sciences, West Boothbay Harbor, ME
Venue:
WACV-MOTION '05 Proceedings of the Seventh IEEE Workshops on Application of Computer Vision (WACV/MOTION'05) - Volume 1 - Volume 01
Year:
2005

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Abstract

Earth's oceans are a soup of living micro-organisms known as plankton. As the foundation of the food chain for marine life, plankton are also an integral component of the global carbon cycle which regulates the planet's temperature. In this paper, we present a technique for automatic identification of plankton using a variety of features and classification methods including ensembles. The images were obtained in situ by an instrument known as the Flow Cytometer And Microscope (FlowCAM), that detects particles from a stream of water siphoned directly from the ocean. The images are of necessity of limited resolution, making their identification a rather difficult challenge. We expect that upon completion, our system will become a useful tool for marine biologists to assess the health of the world's oceans.