Local feature extraction in Log-Polar images

Abstract

We propose two different strategies to compute edges in the log-polar (cortical) domain. The space-variant processing is obtained by applying local operators (e.g. local derivative filters) directly on the logpolar images, or by embedding the same operators into the log-polar mapping, thus obtaining a cortical representation of the Cartesian features. The two approaches have been tested by taking into consideration three standard algorithms for edge detection (Canny, Marr-Hildreth and Harris), applied onto the BSDS500 dataset. Qualitative and quantitative comparisons show a first indication of the validity of the proposed approaches.