Fusion for Evaluation of Image Classification in Uncertain Environments
  We present in this article a new evaluation method for classification and
segmentation of textured images in uncertain environments. In uncertain
environments, real classes and boundaries are known with only a partial
certainty given by the experts. Most of the time, in many presented papers,
only classification or only segmentation are considered and evaluated. Here, we
propose to take into account both the classification and segmentation results
according to the certainty given by the experts. We present the results of this
method on a fusion of classifiers of sonar images for a seabed
characterization.
