This paper applies computer vision techniques to underwater video images of bioluminescent biota for quantifying, tracking, and identification. Active contour models are adapted for computerized image segmentation, labeling, tracking, and mapping of the bioluminescent plankton recorded by low-light-level video techniques. The system automatically identifies luminous events and extracts features such as duration, size, and coordinates of the point of impact, and uses this information to taxonomically classify the plankton species.
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This manuscript is available at http://ieeexplore.ieee.org/ and may be cited as: Kocak, D. M., da Vitoria Lobo, N., & Widder, E. A. (1999). Computer vision techniques for quantifying, tracking, and identifying bioluminescent plankton. IEEE Journal of Oceanic Engineering, 24(1), (pp. 81-95). doi:10.1109/48.740157
Florida Atlantic University. Harbor Branch Oceanographic Institute contribution #1261.