ImageMap: an image indexing method based on spatial similarity

Author

Petrakis, Euripides G M ; Faloutsos, Christos ; Lin, King-Ip David

Author_Institution

Dept. of Comput. Eng., Tech. Univ. of Crete, Chanea, Greece

Volume

14

Issue

5

fYear

2002

Firstpage

979

Lastpage

987

Abstract

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.

Keywords

data mining; data visualisation; database indexing; graph theory; image representation; medical image processing; medical information systems; query processing; visual databases; ARG editing distance; Attributed Relational Graphs; ImageMap; clustering; data mining; data visualization; database indexing; image content representation; image databases; image indexing method; medical images; object interrelationships; queries by example; search; sequential scanning; similarity searching; spatial similarity; Biomedical imaging; Content management; Data mining; Data visualization; Image databases; Image retrieval; Image storage; Indexing; Relational databases; Visual databases;

fLanguage

English

Journal_Title

Knowledge and Data Engineering, IEEE Transactions on

Publisher

ieee

ISSN

1041-4347

Type

jour

DOI

10.1109/TKDE.2002.1033768

Filename

1033768