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This paper presents a model-based method for colour-based recognition of objects from a large database. The algorithm is based on the assumption that surface reflectances of objects in the model database follow the extended dichromatic model proposed by Shafer [Sha84]. Adoption of the dichromatic model allows recovery of body colour - the component of sensor responses (RGB-values) that is independent of scene geometry and illumination intensity. Both theoretical studies [Hea89b] and experiments [LB90][KSK88] confirm that Shafer's model gives a suitable approximation for reflectances of a wide range of materials. Instead of using traditional techniques (eg. clustering, split-and-merge) to obtain regions of 'similarly' coloured pixels followed by classification a novel approach is argued for. First, for each pixel a list of models with nonzero aposteriori probabilities P (model i jbody colour) is computed using Bayes formula. Next, regions are formed by grouping pixels with identical mos..