Using clustering and visualization for refining the results of a WWW image search engine
Proceedings of the 1998 workshop on New paradigms in information visualization and manipulation
Integration of Image Matching and Classification for Multimedia Navigation
Multimedia Tools and Applications
AMORE: A World Wide Web image retrieval engine
World Wide Web
Supporting efficient multimedia database exploration
The VLDB Journal — The International Journal on Very Large Data Bases
Computing, explaining and visualizing shape similarity in content-based image retrieval
Information Processing and Management: an International Journal
Computing, explaining and visualizing shape similarity in content-based image retrieval
Information Processing and Management: an International Journal
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The availability of large image databases and retrieval by content has imposed the requirement for indexing procedures to allow a fast pruning of the database items. Indexing of shapes is particularly challenging owing to the difficulty in deriving a similarity measure that supports clustering of shapes according to human perceptual similarity. In this paper we present a technique which exploits a multiscale analysis of shapes, to derive a hierarchical shape representation in which shape details are progressively filtered out while shape characterizing elements are preserved. To provide the necessary degree of robustness with respect to shape variability fuzzy sets have been used to describe the visual appearance of shape parts. A graph-like index structure is derived by clustering shapes sharing similar part descriptions. Results of indexing for a sample database are reported, with efficiency and effectiveness measures.