Automatic Plankton Image Recognition

Plankton form the base of the food chain in the ocean and are fundamental to marine ecosystem dynamics. The rapid mapping of plankton abundance together with taxonomic and size composition is very important for ocean environmental research, but difficult or impossible to accomplish using traditional techniques. In this paper, we present a new pattern recognition system to classify large numbers of plankton images detected in real time by the Video Plankton Recorder (VPR), a towed underwater video microscope system. The difficulty of such classification is compounded because: 1) underwater images are typically very noisy, 2) many plankton objects are in partial occlusion, 3) the objects are deformable and 4) images are projection variant, i.e., the images are video records of three-dimensional objects in arbitrary positions and orientations. Our approach combines traditional invariant moment features and Fourier boundary descriptors with gray-scale morphological granulometries to for...

• Type: Journal
• Year: 1998
• Where: AIR
• Authors: Xiaoou Tang, W. Kenneth Stewart, He Huang, Scott M. Gallager, Cabell S. Davis, Luc Vincent, Marty Marra
• Keywords: AIR 1998, Plankton, Plankton Images, Video Plankton Recorder