Paper
27 December 2000 Thematico-visual image retrieval: how to deal with partially indexed corpora
Gerald Duffing
Author Affiliations +
Proceedings Volume 4311, Internet Imaging II; (2000) https://doi.org/10.1117/12.411892
Event: Photonics West 2001 - Electronic Imaging, 2001, San Jose, CA, United States
Abstract
It becomes very easy to access large amounts of images when surfing the Internet. All images, however, are not always thematically indexed. We think that partially thematically indexed corpora can be organized in a way that facilitates retrieval. We assume that, concerning visual properties, the corpus is totally indexed by means of generic features. Based on these indexes, a hierarchical clustering technique is used to bring together images that share some similarities: two distinct structures are built (dendrograms). We propose a new retrieval strategy based ona virtual image that captures the user's need along the retrieval session, taking into account both thematic and visual aspects. Clusters are successively selected in each dendrogram. A combined method, called tunnels, allows dendrograms cooperation. Images are then ranked according to the virtual image. After each retrieval step, the virtual image is enriched within a relevance feedback process. Theme, color and general layout of each images can be rated and the query is updated accordingly. In our experiments, we used two different corpora (2470 and 1100 images) to assess the performance of our thematico- visual approach within different indexing conditions. Experimentation results confirm the relevance of our approach and suggests improvement possibilities.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Gerald Duffing "Thematico-visual image retrieval: how to deal with partially indexed corpora", Proc. SPIE 4311, Internet Imaging II, (27 December 2000); https://doi.org/10.1117/12.411892
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KEYWORDS
Visualization

Image retrieval

Image processing

Image visualization

Internet

Feature extraction

Image analysis

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