Rank correlation as illumination invariant descriptor for color object recognition

In this paper, we propose a compact illumination invariant color descriptor. Recent papers have shown that the rank measures of the pixels within a color image are invariant across illumination changes. We exploit this characteristic by measuring the rank correlation between different color components for pixels located at a particular distance from each other. This measure which takes into account both the color distribution and the spatial interactions between the pixels is stable across illumination changes. Furthermore, we show that 18 correlation measures are almost sufficient to discriminate 1000 objects and provide better results than classical invariant indexes which require much more memory space.