Classifying image texture with artificial crawlers

Abstract

This work presents a novel approach to image texture classification, which involves a model of artificial organisms i.e. artificial crawlers (ACrawlers) and a series of evolution curves representing the features of the texture. The distributed ACrawlers locally interact with their living environment, i.e. textured regions, and each ACrawler acts according to a set of homogenous rules for isotropic motion, energy absorption and colony formation etc. The ACrawlers evolve through natural selection, which produces the specific curves of agent evolution, habitant settlement, and colony formation as well as the scale distribution of all colonies. The feasibility and effectiveness of the proposed method have been demonstrated by experiments.