Abstract
This paper presents a morphological classifier with application to color image segmentation. The basic idea of a morphological classifier is to consider that a color histogram is a 3D gray-level image and that morphological operators can be applied to modify this image. The final objective is to extract clusters in color space, that is, identify regions in the 3D image. In this paper, we particularly focus on a powerful class of morphology-based filters called levellings to transform the 3D histogram-image to identify clusters. We also show that our method gives better results than the ones of state-of-the-art methods.