We present an efficient indexing/matching algorithm that is independent of the changes in the illuminant color and the geometric conditions for 3-D object with multiple colors. The color contents of an object can be represented by the peak coordinates in the chromaticity histogram space corresponding to the distinct colors in an image. The visible color areas and their relative sizes of the histograms may change with viewing conditions, but the coordinates of local maxima remain stable. However, a change in illumination color results in a deformation of the chromaticity distribution so as to degrade the performance of color recognition. In order to discount lighting change, we define a chromatic invariant that normalizes the chromaticities of the histogram peaks by the norm of each channel. Therefore, the normalized coordinates of the peaks are stable to the changes in illumination color, scaling, rotation, partial occlusion, viewing direction, and deformation. Test results on a database of diverse images show that the chromatic invariant yields excellent recognition rate even when the illuminant color and geometric conditions vary substantially.