International Business Machines Corporation

William Robinson Equitz

Ronald Jason Barber

Myron Dale Flickner

Dragutin Petkovic

Peter C Yanker

Carlton Wayne Niblack

Bradley J Beitel

Rakesh Agrawal

Arun N Swami

Christos Faloutsos

Thomas R Work

Thomas Randolph Work

Images in an image database are searched in response to queries which include the visual characteristics of the images such as colors, textures, shapes, and sizes, as well as by textual tags appended to the images. Queries are constructed in an image query construction area in response to values of representations of the visual characteristics and to locations of the representations in the image query construction area.

Image query system and method

A high dimensional indexing method is disclosed which takes a set of objects that can be viewed as N-dimensional data vectors and builds an index which treats the objects like k-dimensional points. The method first defines and applies a set of feature extraction functions that admit some similarity measure for each of the stored objects in the database. The feature vector is then transformed in a manner such that the similarity measure is preserved and that the information of the feature vector v is concentrated in only a few coefficients. The entries of the feature vectors are truncated such that the entries which contribute little on the average to the information of the transformed vectors are removed. An index based on the truncated feature vectors is subsequently built using a point access method (PAM). A preliminary similarity search can then be conducted on the set of truncated transformed vectors using the previously created index to retrieve the qualifying records. A second search on the previously retrieved set of vectors is used to eliminate the false positives and to get the results of the desired similarity search.

Method for high-dimensionality indexing in a multi-media database

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Palo Alto, CA, United States of America

William Robinson Equitz