ANN: Digital Image Analysis with Swarm Intelligence
Vitorino RAMOS
on Digital Image Habitats, in International Journal of Lateral
Computing, IJLC, vol. 2, no 1, pp. 1-8, ISSN 0973-208X, Dec. 2005.
PDF: http://alfa.ist.utl.pt/~cvrm/staff/vramos/Vramos-WCLC05b.pdf
ABSTRACT: Artificial life models, swarm intelligent and evolutionary
computation algorithms are usually built on fixed size populations.
Some studies indicate however that varying the population size can
increase the adaptability of these systems and their capability to
react to changing environments. In this paper we present an extended
model of an artificial ant colony system designed to evolve on digital
image habitats. We will show that the present swarm can adapt the size
of the population according to the type of image on which it is
evolving and reacting faster to changing images, thus converging more
rapidly to the new desired regions, regulating the number of his image
foraging agents. Finally, we will show evidences that the model can be
associated with the Mathematical Morphology Watershed algorithm to
improve the segmentation of digital grey-scale images.
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