Semantically homogeneous segmentation with nonparametric region competition

Presents a nonparametric region competition algorithm which combines scale-space clustering and region competition to segment the image. It also proposes a formal and general procedure to automatically find the initial regions. Our algorithm can also segment an image into regions which are not homogeneous in the sense of statistics, but is homogeneous in the sense of semantics with respect to the segmentation context.