Texture similarity using periodically extended and adaptive curvelets

Abstract

This paper presents a new method for texture based image retrieval. The proposed algorithm uses a periodically extended variant of the curvelet transform. The sum of the absolute value of differences in the mean and standard deviation between curvelet wedges representing the query image and the test image is used as the distance index. Performance improvement is demonstrated using the CUReT database, where the proposed algorithm significantly outperforms previously proposed methods that were based on Curvelet, Gabor, LBP, and wavelet features. We also show that adapting curvelet tiles increases the performance of the proposed method.