Color is an important cue both in machine vision and image processing applications, despite its dependence upon illumination changes. We propose a color constancy algorithm that estimates both the set and the likelihood of feasible color mappings in respect to their frequency and effectiveness. The best among this set is selected to rendered back image colors as seen under a canonical light. Experiments were done to evaluate its performance compared to Finlayson’s 2D gamut–mapping algorithm, outperforming it. Our approach is a helpful alternative wherever illumination is poorly known since it employs only image data.

This work was supported by the project 'Integration of robust perception, learning, and navigation systems in mobile robotics' (J-0929).

International Conference on Image Analysis and Recognition (ICIAR), 2005, Toronto (Canada)

Peer Reviewed