Fuzzy relaxation labeling reconsidered

Relaxation labeling is an iterative scheme for parallel information fusion forcing neighborhood constraint satisfaction. In the seminal paper of Rosenfeld et.al.[1] the authors discussed various models for relaxation labeling: discrete, probabilistic, non-linear probabilistic and fuzzy. Since then many new relaxation labeling schemes have been proposed only a few of which are incorporating methodologies from fuzzy set theory. It is shown that this is partly due to the traditional, but questionable classification of relaxation labeling schemes. A new classification is introduced which clarifies the role of fuzzy relaxation labeling. The new classification scheme is complemented by the introduction of a whole range of new fuzzy relaxation operators.