We measured accuracy of object identification across illuminations on the basis of color cues. Four similarly shaped real objects, three of the same reflectance, were separated into pairs under distinct colored real lights. Observers were asked to pick the odd object. Correct and incorrect identifications formed systematic patterns that could not be explained by color-constancy, contrast-constancy, inverse-optics or neural-signal matching algorithms. The pattern of results were simulated by an algorithm that purposely made the incorrect assumption that color constancy holds, and used similarity between perceived object colors, along the difference vector between illuminant colors, to identify objects of the same reflectance across illuminants. The visual system may use this suboptimal strategy because the computational costs of an optimal strategy outweigh the benefits of more accurate performance.