Mining Spatial Association Rules from Image Databases

نویسندگان

  • Tzung-Pei Hong
  • Tien-Chin Wang
  • Been-Chian Chien
چکیده

In this paper, we propose a mining approach for efficiently finding implicit spatial relations of objects in images. An effective representation for spatial relations is first designed, from which primary spatial relations can be easily obtained. The proposed primary spatial relations have a good characteristic of symmetry, which can greatly reduce the number of candidate itemsets in the mining process. An image mining algorithm is then developed to find the association rules of spatial relations among objects based on the representation. The proposed algorithm first mines object associations and then uses them to find spatial relation associations. The association rules derived may provide some spatial information to appropriate analyzers.

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تاریخ انتشار 2003