Rotation invariant texture features using rotated complex wavelet for content based image retrieval

Abstract

A new rotationally invariant texture feature extraction method is introduced that utilizes the dual tree rotated complex wavelet filters (DT-RCWF) and dual tree complex wavelet transform (DT-CWT) jointly. A new two-dimensional rotated complex wavelet filter is designed with a complex wavelet filter coefficient. Decomposing the image with DT-RCWF and DT-CWT jointly gives shift invariant subbands oriented in twelve different directions. Isotropic rotationally invariant features are extracted from these subbands. The performance of image retrieval with the proposed features on rotated and nonrotated image databases is compared with the existing method. Experimental results show that the proposed rotation-invariant texture features are more robust and outperform the other existing methods.