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GraphTheoretic Clustering for Image Grouping and Retrieval Selim Aksoy and Robert M. Haralick
 

Summary: Graph­Theoretic Clustering for Image Grouping and Retrieval
Selim Aksoy and Robert M. Haralick
Intelligent Systems Laboratory
Department of Electrical Engineering
University of Washington
Seattle, WA 98195-2500
{aksoy,haralick}@isl.ee.washington.edu
Abstract
Image retrieval algorithms are generally based on the
assumption that visually similar images are located close
to each other in the feature space. Since the feature vec-
tors usually exist in a very high dimensional space, a para-
metric characterization of their distribution is impossible,
so non-parametric approaches, like the k-nearest neighbor
search, are used for retrieval.
This paper introduces a graph­theoretic approach for
image retrieval by formulating the database search as a
graph clustering problem by using a constraint that re-
trieved images should be consistent with each other (close
in the feature space) as well as being individually similar

  

Source: Aksoy, Selim - Department of Computer Engineering, Bilkent University

 

Collections: Computer Technologies and Information Sciences