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Summary: Content-based Image Database Retrieval Using
Variances of Gray Level Spatial Dependencies
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
http://isl.ee.washington.edu
Abstract. In this paper, we discuss how we use variances of gray level
spatial dependencies as textural features to retrieve images having some
section in them that is like the user input image. Gray level co-occurrence
matrices at five distances and four orientations are computed to measure
texture which is defined as being specified by the statistical distribution
of the spatial relationships of gray level properties. A likelihood ratio
classifier and a nearest neighbor classifier are used to assign two images
to the relevance class if they are similar and to the irrelevance class if they
are not. A protocol that involves translating a K × K frame throughout
every image to automatically construct groundtruth image pairs is pro-
posed and performance of the algorithm is evaluated accordingly. From
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