A Strategy for Boundary Detection Combining Region and Edge Information

A method to detect boundaries in in natural color images is here proposed, combining edge information and region information. This unsupervised fully automatic process uses edge map information to eliminate false boundaries in the image region map, and region map information to remove noise in the image edge map. Thus, it integrates these two maps into a single one to get the final result. This proposal is extensively compared to the multi-label graph cut approach, since both approaches are unsupervised and fully automatic, as well as receive the same two inputs, although performing different processing. Experiments performed on a large set of natural color images were the base for such comparison. The results show that the approach here proposed is promising, besides allowing interesting interpretations about boundary detection.