Fluorescent surfaces are common in the modern world, but they present problems for machine color constancy because fluorescent reflection typically violates the assumptions needed by most algorithms. The complexity of fluorescent reflection is likely one of the reasons why fluorescent surfaces have escaped the attention of computational color constancy researchers. In this paper we take some initial steps to rectify this omission. We begin by introducing a simple method for characterizing fluorescent surfaces. It is based on direct measurements, and thus has low error and avoids the need to develop a comprehensive and accurate physical model. We then modify and extend several modern color constancy algorithms to address fluorescence. The algorithms considered are CRULE and derivatives, Color by Correlation, and neural net methods. Adding fluorescence to Color by Correlation and neural net methods is relatively straight forward, but CRULE requires modification so that its complete reliance on diagonal models can be relaxed. We present results for both synthetic and real image data for fluorescent capable versions of CRULE and Color by Correlation, and we compare the results with the standard versions of these and other algorithms.