Influence of Basic Belief Assignments Construction on the Behaviour of a Fusion System for Tree Species Recognition
Abstract
In the framework of belief functions, basic belief assignments building is an important step that should be made carefully since it can greatly influence the performances of a system. In the context of tree species recognition through a leaf and a bark, we analyze the impact of Bayesian as well as consonant basic belief assignments in the case of fusion of uncertain and not equally reliable sources of information. We show that, despite the imprecision they bring, consonant belief functions prove their performances in managing and representing uncertain information. In this application, photos of leaves and barks are the sources of information allowing tree species recognition.