A supervised segmentation scheme for cancerology color images

In this paper, we describe a new scheme for color image segmentation based on supervised pixel classification methods. Using color pixel classification alone does not extract accurately enough color regions, so we suggest to use a strategy based on four steps : simplification, pixel classification, marker extraction and color watershed growing. We detail in this paper the pixel classification and marker extraction steps. A quantitative measure, which evaluates the resulting classifications and segmentations with respect to a set of reference images, is presented. Our strategy is suitable for the detection of color objects in noisy environment and is particularly efficient on cytological color images.