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Using Texture in Image Similarity and Retrieval Selim Aksoy and Robert M. Haralick

Summary: Using Texture in Image Similarity and Retrieval
Selim Aksoy and Robert M. Haralick
Intelligent Systems Laboratory
Department of Electrical Engineering
University of Washington
Seattle, WA 98195-2500
Abstract. Texture has been one of the most popular representations in image retrieval.
Our image database retrieval system uses two sets of textural features, first one being the
line-angle-ratio statistics which is a texture histogram computed from the properties of the
surroundings and the spatial relationships of intersecting lines, second one being the variances
of gray level spatial dependencies computed from co-occurrence matrices. This paper also
discusses a line selection algorithm to eliminate insignificant lines and statistical feature
selection methods to select the best performing subset of features. Average precision is used
to evaluate the retrieval performance in comparative tests with three other texture analysis
algorithms. Results show that our method is fast and effective with an average precision of
0.73 when 12 images are retrieved.
1 Introduction
Image databases are becoming increasingly popular due to large amount of images that
are generated by various applications and the advances in computer technology. Initial work


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


Collections: Computer Technologies and Information Sciences