Introduction of spatial information within the context of evidence theory

We propose a method to introduce spatial information within the context of pattern recognition by the mean of evidence theory. Indeed, we can consider that each neighbor brings some information useful to determined the class of a pattern to classify. We propose to introduce such information through the Dempster´s (1967) combination rule. This combination, which takes into account the distance between neighbors, provides a more accurate modeling of the information and improves the classification process of the data. We illustrate the interest and the impact of this method through the problem of segmentation of multi-echo magnetic resonance (MR) images. In particular, we show that the segmentation results are more accurate and that some ambiguities of classification are resolved.