Image analysis using attributed fuzzy tournament matching algorithm

Attributed Fuzzy Tournaments (AFT''s) are a special type of attributed fuzzy graphs which are useful to represent uncertainties inherent to many realworld problems. A new algorithm that finds the best fuzzy matching configuration between components of two Attributed Fuzzy Transitive Tournaments (AFTT''s) is proposed. The best fuzzy matching between two AFTT''s is the matching configuration between components of both AFTT''s such that the overall distance measure between two AFTT''s possesses the minimum value. Useful applications of the proposed algorithm can be found in scene matching where the nodes of an AFT represent the objects in the scene and the arcs represent the relationships among the objects. Uncertainties of the image are represented via fuzzy membership values associated with the nodes and arcs. An examples showing the usefulness of the algorithm in pattern matching is shown through image analysis. I.