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Title: Method for the reduction of image content redundancy in large image databases

Abstract

A method of increasing information content for content-based image retrieval (CBIR) systems includes the steps of providing a CBIR database, the database having an index for a plurality of stored digital images using a plurality of feature vectors, the feature vectors corresponding to distinct descriptive characteristics of the images. A visual similarity parameter value is calculated based on a degree of visual similarity between features vectors of an incoming image being considered for entry into the database and feature vectors associated with a most similar of the stored images. Based on said visual similarity parameter value it is determined whether to store or how long to store the feature vectors associated with the incoming image in the database.

Inventors:
 [1];  [2]
  1. Harriman, TN
  2. Knoxville, TN
Issue Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1014516
Patent Number(s):
7,672,976
Application Number:
US Patent Application 11/416,844
Assignee:
UT-Battelle, LLC (Oak Ridge, TN)
DOE Contract Number:  
AC05-96OR22464
Resource Type:
Patent
Country of Publication:
United States
Language:
English

Citation Formats

Tobin, Kenneth William, and Karnowski, Thomas P. Method for the reduction of image content redundancy in large image databases. United States: N. p., 2010. Web.
Tobin, Kenneth William, & Karnowski, Thomas P. Method for the reduction of image content redundancy in large image databases. United States.
Tobin, Kenneth William, and Karnowski, Thomas P. Tue . "Method for the reduction of image content redundancy in large image databases". United States. https://www.osti.gov/servlets/purl/1014516.
@article{osti_1014516,
title = {Method for the reduction of image content redundancy in large image databases},
author = {Tobin, Kenneth William and Karnowski, Thomas P},
abstractNote = {A method of increasing information content for content-based image retrieval (CBIR) systems includes the steps of providing a CBIR database, the database having an index for a plurality of stored digital images using a plurality of feature vectors, the feature vectors corresponding to distinct descriptive characteristics of the images. A visual similarity parameter value is calculated based on a degree of visual similarity between features vectors of an incoming image being considered for entry into the database and feature vectors associated with a most similar of the stored images. Based on said visual similarity parameter value it is determined whether to store or how long to store the feature vectors associated with the incoming image in the database.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2010},
month = {3}
}

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