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ImageMap: an image indexing method based on spatial similarity

Petrakis Evripidis, Lin, K.-I., Faloutsos, C

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URI: http://purl.tuc.gr/dl/dias/DB29B36F-71EB-4B4E-8642-46E764F4AD62
Year 2015
Type of Item Peer-Reviewed Journal Publication
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Bibliographic Citation Euripides G.M. Petrakis, Christos Faloutsos and King-Ip Lin: "ImageMap: An Image Indexing Method Based on Spatial Similarity", IEEE Transactions on Knowledge and Data Engineering, Vol. 14, no. 5, pp. 979-987, Sept./Oct 2002. DOI: 10.1109/TKDE.2002.1033768 https://doi.org/10.1109/TKDE.2002.1033768
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Summary

We introduce ImageMap, as a method for indexing and similarity searching in image databases (IDBs). ImageMap answers "queries by example" involving any number of objects or regions and taking into account their interrelationships. We adopt the most general image content representation, that is, Attributed Relational Graphs (ARGs), in conjunction with the well-accepted ARG editing distance on ARGs. We tested ImageMap on real and realistic medical images. Our method not only provides for visualization of the data set, clustering and data mining, but it also achieves up to 1,000-fold speed-up in search over sequential scanning, with zero or very few false dismissals.

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