Rotation and scale invariant feature extractors

Abstract

This paper deals with texture feature extraction operators, which comprise linear filtering eventually followed by post processing. Robust, rotation and scale invariant texture operators are important for digital image libraries and multimedia databases. A method of rotation and scale-invariant texture classification based on a log polar coordinate system is introduced. Texture is an important clue in region based segmentation of images. Here, we provide analysis and implementation of a set of distortion invariant texture operators viz circular Mellin features (CMF). The CMF represent the spectral decomposition of the image scene in the polar log coordinate system and are invariant to both scale and orientation of the target texture pattern. The image and CMF are correlated followed by magnitude detection based on thresholding. The CMF extractors have a functional form that is similar to Gabor functions; they have distortion invariant characteristics, unlike Gabor functions, which makes them more suitable for texture segmentation.