Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2067/440
Titolo: Structured Knowledge Representation for Image Retrieval
Autori: Di Sciascio, Eugenio
Donini, Francesco Maria 
Mongiello, Marina
Parole chiave: Image Retrieval;Knowledge Representation;Artificial Intelligence;Intelligent Systems
Data pubblicazione: apr-2002
Editore: AI Access Foundation and Morgan Kaufmann Publishers
Fonte: Journal of Artificial Intelligence Research 16 (2002) 209-257
We propose a structured approach to the problem of retrieval of images by content and present a description logic that has been devised for the semantic indexing and retrieval of images containing complex objects. As other approaches do, we start from low-level features extracted with image analysis to detect and characterize regions in an image. However, in contrast with feature-based approaches, we provide a syntax to describe segmented regions as basic objects and complex objects as compositions of basic ones. Then we introduce a companion extensional semantics for defining reasoning services, such as retrieval, classification, and subsumption. These services can be used for both exact and approximate matching, using similarity measures. Using our logical approach as a formal specification, we implemented a complete clientserver image retrieval system, which allows a user to pose both queries by sketch and queries by example. A set of experiments has been carried out on a testbed of images to assess the retrieval capabilities of the system in comparison with expert users ranking. Results are presented adopting a well-established measure of quality borrowed from textual information retrieval.
URI: http://hdl.handle.net/2067/440
ISSN: 11076 - 9757
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