Visual metrics: discriminative power through flexibility

An important stage in visual processing is the quantification of optical attributes of the outside world. We argue that the metrics used for this quantification are flexible, and that this flexibility is exploited to optimise the discriminative power of the metrics. We derive mathematical expressions for such optimal metrics and show that they exhibit properties resembling well-known visual phenomena. To conclude, we discuss some of the implications of flexible metrics for visual identification.