ImageMap: An Image Indexing Method Based on Spatial Similarity

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 inter-relationships. 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 dataset, 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.

• Type: Journal
• Year: 2002
• Where: TKDE
• Authors: Euripides G. M. Petrakis, Christos Faloutsos, King-Ip Lin
• Keywords: Image Content Representation, ImageMap, Realistic Medical Images, TKDE 2002