Abstract

The authors describe a constraint-based image understanding system, named COBIUS, for aerial imagery interpretation. COBIUS consists of knowledge bases for domain objects spatial and temporal constraints, control strategies, blackboard areas to instantiate hypotheses of objects and constraints, and an image feature database to fuse results from multiple image segmentation modules. Domain-specific knowledge is represented in terms of generic temporal and spatial constraints. A set of generic constraint manipulation and hypothesis formation rules are used to perform formation, evaluation, propagation, and satisfaction of constraints and hypotheses. More importantly, constraints are represented hierarchically and are no different from the representation of domain objects. This representation avoids time-consuming graph matching processor for image interpretation and provides greater representation modularity. The processing example is presented. >

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