  The sonar images provide a rapid view of the seabed in order to characterize
it. However, in such as uncertain environment, real seabed is unknown and the
only information we can obtain, is the interpretation of different human
experts, sometimes in conflict. In this paper, we propose to manage this
conflict in order to provide a robust reality for the learning step of
classification algorithms. The classification is conducted by a multilayer
perceptron, taking into account the uncertainty of the reality in the learning
stage. The results of this seabed characterization are presented on real sonar
images.
