Image indexing by using a rotation and scale invariant partition

We propose an indexing technique which allows to solve indexing problems due to geometric or photometric transformations, inferred by the different image acquisitions. This approach is based on an invariant partition of the image thanks to the use of interest points (or keypoints) and a characterisation with moments. The research process is based on a similarity measure taking in account a numerical distance and a localisation criterion. This work is based on a local characterisation of the image, we use the interest points to build a triangular partition. We associate to each polygon a vector containing its photometric properties. The research process is particularly important, it uses traditional spatial relations and integrate them with a numerical distance to calculate a score associated to each image.