Title

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

Authors

Authors

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

Comments

Authors: contact us about adding a copy of your work at STARS@ucf.edu

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

Share

COinS