Knowledge-based image segmentation using swarm intelligence techniques

Abstract

Intelligent techniques such as swarm intelligence techniques rarely have been used for image segmentation or boundary detection. The limited increasing number of agents in the environment and how to find efficiently the right threshold in an image, develop a flexible design, and fully autonomous system that supports different platforms makes the task challenging. Considering challenges this paper presents a swarm-based intelligent technique for image segmentation that is based on a fully agent-based model system, called swarm intelligence-based image segmentation (SIBIS). SIBIS adopts a cellular automata technique where the swarm of agents navigate through the image and operate on their pixels and local regions. Three features such as swarm intelligence, agent-based modelling and cellular automata are integrated to make SIBIS efficient. SIBIS system can find the image segmentation threshold automatically without changing the background or the texture of the image.