Hierarchical processing of structural information in artificial intelligence

Most problems in signal processing have structural aspects which are difficult to solve using general methods. Use of ad hoc methods is limited to cases where structural aspects are easy to re-solve. An approach for hierarchical processing is described whereby structural aspects are resolved simultaneously with the analysis of data values. An effective use of a hierarchical structure puts strong restrictions upon information representation and operations. Information is represented in terms of compatibility and incompatibility of events, combined with a measure of confidence. Operations are of type symmetry operations, which allow data compression, context control and have a good descriptive power. These methods have been tested in various problems in image analysis and image processing with satisfactory results.