A color space metric that is useful for computer vision is developed. It can be applied to images sensed using color filters (e.g. R, G, B). This metric is defined in terms of the spectral characteristics of the filters and camera and accounts for their noise properties. The metric is designed to respond to material changes while remaining insensitive to geometric variation in the scene. The color distance function is derived as an estimate of the distance between normalized spectral power distributions. Components of this distance are weighted to account for sensor noise properties. A color metric has several possible uses in a computer vision system. It is useful for detecting color edges, classifying intensity edges, and estimating color variation within image regions. The usefulness of this color metric is demonstrated by evaluating its performance on real images. >