Multiscale shape description with laplacian profile and fourier transform

Abstract

We propose a new local multiscale image descriptor of variable size. The descriptor combines Laplacian of Gaussian values at different scales with a Radial Fourier Transform. This descriptor provides a compact description of the appearance of a local neighborhood in a manner that is robust to changes in scale and orientation. We evaluate this descriptor by measuring repeatability and recall against 1-precision with the Affine Covariant Features benchmark dataset and as well as with a set of textureless images from the MIRFLICKR Retrieval Evaluation dataset. Experiments reveal performance competitive to the state of the art, while providing a more compact representation.