Multibiometrics Feature Level Fusion by Graph Clustering
This paper presents a feature level fusion approach which uses the improved K-medoids clustering algorithm and isomorphic graph for face and palmprint biometrics. Partitioning Around Medoids (PAM) algorithm is used to partition the set of n invariant feature points of the face and palmprint images into k clusters. By partitioning face and palmprint images with scale invariant features SIFT points, a number of clusters are formed on both the images. Then on each cluster, an isomorphic graph is drawn. Most probable pair of graphs is searched using iterative relaxation algorithm from all possible isomorphic graphs for a pair of corresponding face and palmprint images.