Scale and rotation invariant texture features from the dual-tree complex wavelet transform

Abstract

Image segmentation can be viewed as the process of classifying regions in a picture into groups with common properties (e.g., texture). A difficulty arising is that a common texture can be classified differently when viewed at different scales and rotated viewpoints. The paper presents a feature vector based on the DT-CWT (dual-tree complex wavelet transform) (Kingsbury, N., Applied and Computational Harmonic Anal., vol.10, p.234-53, 2001) that is invariant to scale and rotation. The promising image segmentation results (without cleaning misclassified regions) demonstrate the suitability of this feature vector in representing texture.