Summary: A GraphTheoretic Approach to Image
Selim Aksoy and Robert M. Haralick
Intelligent Systems Laboratory
Department of Electrical Engineering
University of Washington
Seattle, WA 98195-2500 U.S.A.
Abstract. Feature vectors that are used to represent images exist in a
very high dimensional space. Usually, a parametric characterization of
the distribution of this space is impossible. It is generally assumed that
the features are able to locate visually similar images close in the feature
space so that non-parametric approaches, like the k-nearest neighbor
search, can be used for retrieval.
This paper introduces a graphtheoretic approach to image retrieval by
formulating the database search as a graph clustering problem to increase
the chances of retrieving similar images by not only ensuring that the
retrieved images are close to the query image, but also adding another
constraint that they should be close to each other in the feature space.