In multi-agent systems, the reactive approach emphasizes on the individual simplicity in comparison to the collective complexity of the task being performed. However, to apply such an approach to solve a problem, the components of the multi-agent system have to be designed such as the society is able to fulfill its requirements with a reasonable efficiency. Taking inspiration from natural swarm systems is a way to solve this conception issue. This article presents a new swarm mechanism inspired by the simulation of the collective weaving in social spiders. The main difference with existing mechanisms is the possibility in the spider model to integrate non-local information in local processing. In this paper, we describe the simulation model and its transposition to a specific application case: the extraction of regions in an image. Some experiments conducted on real gray level images are detailed together with studies about the influence of the different algorithm parameters on its performance.