Spatial relations among fuzzy subsets of an image

As the use of fuzzy set theory in computer vision continues to grow, there is an increased need for methodologies and formalisms to extract and manipulate this type of uncertainty from a digital image. The concepts involved in spatial relationships among image objects and regions have been investigated and acknowledged as being vague and ambiguous. Algorithms which produce fuzzy, rather than crisp, partitions of the plane place even greater demands on any approach to describe spatial relationships. The authors present an approach based on the concept of dominance in fuzzy set theory for modeling simple spatial relationships among crisp and fuzzy subsets of an image.<>