A genetic algorithm based image segmentation for image analysis

In this paper a new genetic algorithm (GA) based image segmentation method is proposed for image analysis. This method using a mean square error (MSE) based criterion can segment an image into some regions, while estimating a suitable region representation. The criterion is defined as MSE caused by interpolating each region of an observed image with a parametric model. Since the criterion is expressed with not only the parameters of the model but also shape and location of the regions, the criterion can not be easily minimized by the usual optimization methods, the proposed method minimizes the criterion by a GA. The proposed method also includes a processor to eliminate fragile regions with the Markov random field (MRF) model. Though the thresholds of the existent methods negatively affect image segmentation results; since no thresholds are required in the proposed method, it segments images more accurately than the existent methods.