Steerable filter in frequency domain with rose curve

Feature extraction in image processing area is a vital part for further processes in this area. Feature extraction from images is mainly conducted by the filters both in spatial domain and frequency domain. Finding suitable, especially when directional features are in question, in spatial domain is a difficult task. However, feature extraction in frequency domain is more flexible since directions are more obvious in this area. For feature extraction in frequency domain, several methods have been proposed and actively been in use image processing area. One of these methods is Contourlet Transform which does not offer easy direction selectivity. In other words, directions are constant in Contourlet Transform. Another widely used method is 2D Gabor Filter. Although 2D Gabor Filter has flexibility in direction selection, the method suffers from large number of parameters to decide. In this thesis study, a novel filter for feature extraction in frequency domain using Rose Curve has been proposed. One of the most important properties of the proposed method is angle selectivity. Easiness for the direction selectivity has been achieved by this method. Another property of the proposed method is the number of parameters to decide. The proposed method has only three, easily adjustable parameters. The proposed method has been evaluated on the facial expression classification problem and higher results in terms of different metrics than some of the state of the arts methods in the literature were obtained.