Local norm features based on ridgelets transform

Abstract

We propose a set of shape descriptors for image retrieval of graphic documents based on the ridgelets transform, which can be seen as a combination of the Radon transform and the wavelets transform. It is especially well suited to detect linear features, the most relevant features in graphic documents. It also provides a multiscale representation, useful for indexing and retrieval purposes. From the ridgelets representation of an image, we have defined a set of local norm descriptors based on computing a norm over some specific areas of the image. This kind of descriptors are very flexible since we can define different sets of descriptors just by changing such areas of influence in the image. We have also defined a combination of descriptors at several scales of decomposition in order to improve retrieval results.