Genetic fusion: application to multi-components image segmentation

In this communication, we propose a new approach which enables to fusion either the results of several segmentation methods of a same image or the different results in the case of a multi-components image. The developed method is based on a genetic algorithm approach which allows to combine segmentation results by taking into account their quality through an evaluation criterion. This criterion provides to quantify a segmentation result without any a priori knowledge such as the ground truth. This approach is applied to segment multi-components images by combining the segmentation results of each component. We show the efficiency of the method through some experimental results on several images.