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Generation of a hierarchical representation for graphic patterns based on grouping

The ability to retrieve by similarity is one powerful way to improve the human interface in an image database. In this paper, graphic patterns constructed as a set of primitive patterns formed from closed regions are the target images. When recognizing this kind of graphic pattern, people perform grouping. The partial patterns formed by this grouping play a major role in the similarity between graphic patterns. Consequently, the partial patterns that result from grouping must be introduced into the image representation as search keys. Furthermore, it would be desirable to have this representation automatically generated. In this paper, we propose a method where a representation in the part-of hierarchy of partial patterns is used as the graphic pattern representation; this representation is generated from the raw image of the graphic pattern. This method uses the rules for visual characteristics for grouping in humans. First, partial patterns are formed by bottom-up processing. Then, by comparing the stability of the final partial patterns, partial patterns that do not match human perception are deleted and missing partial patterns are searched for and added. A prototype system was built based on this method, and the method's adequacy was verified.