Quantitative analysis of properties and spatial relations of fuzzy image regions

Properties of objects and spatial relations between objects play an important role in rule-based approaches for high-level vision. The partial presence or absence of such properties and relationships can supply both positive and negative evidence for region labeling hypotheses. Similarly, fuzzy labeling of a region can generate new hypotheses pertaining to the properties of the region, its relation to the neighboring regions, and, finally, hypotheses pertaining to the labels of the neighboring regions. A unified methodology that can be used to characterize both properties and spatial relationships of object regions in a digital image is presented. The methods proposed for computing the properties and relations of image regions can be used to arrive at more meaningful decisions about the contents of the scene