Image segmentation is an important process in image processing.The quality of image segmentation directly affects the following analysis and recognition.Because evolutionary agent has some advantages such as self-fitness non-linear mapping and ability of parallel disposal

this paper presents an autonomous agent-based image segmentation approach.In this approach

a digital image is viewed as a two-dimensional cellular environment in which the agents inhabit and attempt to label homogeneous segments.The agents rely on some reactive behaviors such as breeding and diffusion.The agents that are successful in finding the pixels of a specific homogeneous segment will breed offspring agents inside their neighboring regions.Hence

the offspring agents will become likely to find more homogeneous-segment pixels.In the mean time

the unsuccessful agents will be inactivated without further search in the environment.It can be seen from our experiment in medical chest CT image and brain MRI image that this method can better extract interesting regions.