In this paper we present a method of segmentation using a multiagent system, and an application to fish otolith growth ring detection. The otoliths images are composed of alternative concentric dark and light rings, the number of which increases with the age of the fish. Up to now, the identification of growth rings, for age estimation, is routinely achieved by human readers, but this task is tedious and depends on the reader's subjectivity. The system proposed here is composed of several agents whose individual task is to detect local extremes on a grayscale image. For this aim the agents are provided with sensors on the gray levels of the image. By computing the mean gray level of two sensors placed in front of it, the agent, if it searches for light rings (respectively dark) will decide to turn in the direction of the lighter (respectively darker) sensor. The path of the agents has been tested as a roof edge detector, using the Canny criteria: good detection, good localization, and low multiple response, in order to choose the best parameters ruling the agents behavior, according to the image structures. Tests have been first achieved on synthetic images, and then on otoliths images.

Date Published: 3 March 2000
PDF: 12 pages
Proc. SPIE 3961, Nonlinear Image Processing XI, (3 March 2000); doi: 10.1117/12.379393

Published in SPIE Proceedings Vol. 3961:
Nonlinear Image Processing XI
Edward R. Dougherty; Jaakko T. Astola, Editor(s)