Computer vision techniques for quantifying, tracking, and identifying bioluminescent plankton

    Authors

    D. M. Kocak; N. D. Lobo;E. A. Widder

    Comments

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    Abbreviated Journal Title

    IEEE J. Ocean. Eng.

    Keywords

    active contour models; bioluminescent plankton; computer vision; tracking; undersea taxonomic classification; ACTIVE CONTOUR; IMAGES; MODELS; Engineering, Civil; Engineering, Ocean; Engineering, Electrical &; Electronic; Oceanography

    Abstract

    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. This automatic classification can aid oceanographic researchers in characterizing the in situ spatial and temporal relationships of these organisms in their underwater environment. Experiments with real oceanographic data are reported. The results indicate that the approach yields performance comparable to human expert level capability. Furthermore, because the described technique has the potential to rapidly process vast quantities of video data, it may prove valuable for other similar applications.

    Journal Title

    Ieee Journal of Oceanic Engineering

    Volume

    24

    Issue/Number

    1

    Publication Date

    1-1-1999

    Document Type

    Article

    Language

    English

    First Page

    81

    Last Page

    95

    WOS Identifier

    WOS:000078150300008

    ISSN

    0364-9059

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