Invariant Salient Region Selection and Scale Normalization of Image

Abstract

Scale estimation is important in image and vision computing. We propose in this paper an invariant salient region selection and scale normalization method which is robust to rotation, scaling, translation and cropping. This new method is based on the first and second order invariant geometric moments calculated from an intensity difference map. The first-order moments are used to obtain invariant circular regions for different scale hypotheses, while a second-order moment is chosen as region descriptor to select the most salient scale. The image is normalized by scale of the selected salient region. Experiments demonstrate effectiveness of this method