A Quantitative Comparison of Speed and Reliability for Log-Polar Mapping Techniques

A space-variant representation of images is of great importance for active vision systems capable of interacting with the environment. A precise processing of the visual signal is achieved in the fovea, and, at the same time, a coarse computation in the periphery provides enough information to detect new saliences on which to bring the focus of attention. In this work, different techniques to implement the blind-spot model for the log-polar mapping are quantitatively analyzed to assess the visual quality of the transformed images and to evaluate the associated computational load. The technique with the best trade-off between these two aspects is expected to show the most efficient behaviour in robotic vision systems, where the execution time and the reliability of the visual information are crucial.