A criterion-based image segmentation method with a genetic algorithm

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