Hierarchical image segmentation based on contour dynamics

We propose an image segmentation method based on morphological decomposition and graph-based region merging using contour dynamics. The input image is initially decomposed into a set of primitive homogeneous regions through the morphological watershed transform applied to the image intensity gradient magnitude. This decomposition is represented by a region adjacency graph (RAG) that is input to a hierarchical merging process in which neighboring regions of high similarity are merged. The region similarity criterion is based on the concept of watershed contour dynamics. The robustness of the segmentation to the presence of noise and/or low contrast is improved by a regularization of the contour dynamics. Experimental results on various kinds of synthetic and real images, as well as comparison of the proposed method with other wellknown region merging algorithms are presented