Automatic Query Generation for Content-Based Image Retrieval

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Automatic Query Generation for Content-Based Image Retrieval
We describe a subsystem of a content-based image retrieval (CBIR) environment that supports a user in the definition of image similarity. Out of a single image or a set of query images we refine a query model: a list of feature extraction functions with associated thresholds and weights. The subsystem aims at bridging the gap between a user’s high-level concepts and the low-level visual features employed and at supporting both, the casual user and the expert. The paper investigates and evaluates several approaches for this purpose within a CBIR system for coats of arms. A user may edit any entry of the query model in order to optimize retrieval results by iteration.
Christian Breiteneder, Horst Eidenberger
Added 31 Jul 2010
Updated 31 Jul 2010
Type Conference
Year 2000
Authors Christian Breiteneder, Horst Eidenberger
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