Harald Kosch
ABSTRACT
Commonly used content-based image retrieval systems focus on the problem of finding similar images for a given single query object out of a database of media objects. We consider a similarity-based image join of two image tables, where the image data components are represented by their respective feature vectors. For each image of the first table, similar images are looked up in the second table. Matching tuples are combined. We consider multiple joins which allows one to join a previous join result to another image table, and so on. Thus, each multiple join result tuple contains n images, if n tables are joined. An image of the result tuple is therefore not only similar to the image from its join partner, but also to the image similar to it. In this context, the paper presents processing and optimizing strategies for multiple similarity-based image joins and a cost model for integrating them in a multimedia database. The cost model is validated by an X-tree reference implementation. The presented strategies in this paper are currently been implemented in Oracle Multimedia.
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Index Terms
- Optimizing similarity-based image joins in a multimedia database
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