Area operators for edge detection
In area morphology, the area openclose (AOC) and closeopen (ACO) operations are based on filtering the connected components in the image level sets. Unlike traditional morphology that enforces the shape of the structuring element on image region boundaries, area morphology allows removal of small features without boundary distortion. This study defines ascending and descending objects that depend on the area of the connected components of the level sets. The major contribution of the paper is to define image edges at the boundaries of the ascending and descending objects. From this area morphology approach, thin, closed contours are provided that are suitable for use in image segmentation. A notable strength of the area morphology edge detector is that it does not require the use of a threshold. The edge maps are Euclidean invariant and causal, and yield good performance in terms of edge localization and the suppression of below-scale detail. The results demonstrate the superior performance of the area operator-based edge detection over the conventional techniques.
edge detection segmentation non-linear filters