Color image segmentation based on fuzzy mathematical morphology

In this paper, we present a new color image segmentation method. After a color pixel projection into an attribute space, segmentation consists of detecting the different modes associated with homogeneous regions. In order to detect these modes, we show how a color image can be viewed as a fuzzy set with its associated membership function to a mode which is defined by a color co-occurrence matrix and by mode concavity properties. A newly developed fuzzy morphological transformation is then applied to this membership function in order to identify the modes. The performance of our proposed fuzzy morphological approach is then presented using a test color image and is then compared to the well-known competitive learning algorithm