Depicting classification uncertainty using perception-based color models

Abstract

Fuzzy classification typically assigns a location or an area to a category with some estimated degree of uncertainty. There are strong incentives for depicting uncertainty along with category, and numerous authors have recommended that this be done using progressive desaturation of the entity's color with increasing uncertainty. This article shows that such recommendations cannot be naively applied using color models widely used in computer graphics because colors equally 'saturated' do not appear equally certain. We demonstrate that models based on color perception are preferred, particularly if one wishes to compare uncertainties across classes. We discuss geometrical complications arising with perceptual models that are not present with models closely tied to hardware. An algorithm for selecting colors is presented and illustrated using the model. © 2011 Taylor & Francis.