In this paper, we propose an original approach which allows to recognize objects in color images acquired under uncontrolled illumination conditions. For each pair of images to compare, the scheme consists in evaluating specific color features adapted to this pair. These adapted features are evaluated so that the distributions of adapted colors in the two images are similar only when they contain the same object. Then we propose to analyze the spatial co-occurrences between the adapted features to compute the image indices. Experimental tests on a public image database show the efficiency of this approach in the context of object recognition across illumination changes.