Images of a single object, varying the capture position, can generate smooth deformations in their selfrepresentation. In an image plane, these deformations can be approximated by affine transformations, making it useful to recognize the same object in different angles. We present the RHO-Affine-ORB, an affine invariant feature detector, based on original ORB algorithm adapted to be affine inva...

Imagery registration is a fundamental step, which greatly affects later processes in image mosaic, multi-spectral image fusion, digital surface modelling, etc., where the final solution needs blending of pixel information from more than one images. It is highly desired to find a way to identify registration regions among input stereo image pairs with high accuracy, particularly in remote sensin...

Logo localization and recognition is difficult in natural images due to perspective deformations, varying background, possible occlusions, scaling variability; furthermore, the re–branding induces changes in the logo color palette and spatial distribution. To address this task, we locate keypoints using Affine Difference of Gaussian described by SIFT elliptical features; we construct the class ...

In this paper we describe a system that participated in the fourth benchmarking activity ImageCLEF, in the Robot Vision task, for which we approach the task of topological localization without using a temporal continuity of the sequences of images. We provide details for the state-of-the-art methods that were selected: Color Histograms, SIFT (Scale Invariant Feature Transform), ASIFT (Affine SI...

Using a classical result on algebraic invariants of the unimodular group, we present in this paper some basic geometric affine invariant quantities, and we use them to construct some distinctive descriptors for object detection. Although full affine invariance cannot be guaranteed due to noncommutativity of camera blur with affine maps and the domain problem (that is, the difficulty of finding ...