Computer Science

Automatic in situ identification of plankton

Matthew B. Blaschko, Manning College of Information & Computer Sciences
Gary Holness, Manning College of Information & Computer Sciences
Marwan A. Mattar, Manning College of Information & Computer Sciences
Dimitri Lisin, Manning College of Information & Computer Sciences
Paul E. Utgoff, Manning College of Information & Computer Sciences
Allen R. Hanson, Manning College of Information & Computer Sciences
Howard Schultz, Manning College of Information & Computer Sciences
Edward M. Riseman, Manning College of Information & Computer Sciences
Michael E. Sieracki, Bigelow Laboratory for Ocean Sciences
William M. Balch, Bigelow Laboratory for Ocean Sciences
Ben Tupper, Bigelow Laboratory for Ocean Sciences

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.