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

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Date Issued:
1999
Title: Computer vision techniques for quantifying, tracking, and identifying bioluminescent plankton.
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Name(s): Kocak, D. M., creator
da Vitoria Lobo, N., creator
Widder, Edith A., creator
Harbor Branch Oceanographic Institute
Type of Resource: text
Genre: Article
Issuance: single unit
Date Issued: 1999
Publisher: IEEE
Extent: 16 p.
Physical Description: pdf
Language(s): English
Identifier: 3183711 (digitool), FADT3183711 (IID), fau:5960 (fedora), 10.1109/48.740157 (doi)
Note(s): 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.
Subject(s): Underwater imaging systems
Computer vision
Persistent Link to This Record: http://purl.flvc.org/FCLA/DT/3183711
Links: http://dx.doi.org/10.1109/48.740157
Restrictions on Access: ©1999 IEEE
Host Institution: FAU