An efficient approach to texture-based image retrieval

Abstract

In this article, we present an efficient approach for image retrieval based on the textural information of an image, such as orientation, directionality, and regularity. For this purpose, we apply the nonlinear modified discrete Radon transform to estimate these visual contents. We then utilize texture orientation to construct the rotated Gabor transform for extraction of the rotation-invariant texture feature. The rotation-invariant texture feature, directionality, and regularity are the main features used in the proposed approach for similarity assessment. Experimental results on a large number of texture and aerial images from standard databases show that the proposed schemes for feature extraction and image retrieval significantly outperform previous works, including methods based on the MPEG-7 texture descriptors. © 2008 Wiley Periodicals, Inc.