Cosine-modulated wavelet based texture features for content-based image retrieval

Feature extraction is one of the most important tasks for efficient and accurate image retrieval purpose. In this paper we have presented a Cosine-modulated wavelet transform based technique for extraction of texture features. The major advantages of Cosine-modulated wavelet transform are less implementation complexity, good filter quality, and case in imposing the regularity conditions. Texture features are obtained by computing the energy, standard deviation and their combination on each subband of the decomposed image. To check the retrieval performance, texture database of 1856 textures is created from Brodatz album. Retrieval efficiency and accuracy using Cosine-modulated wavelet based features is found to be superior to other existing methods. (C) 2003 Elsevier B.V. All rights reserved.