Image Matching using Weighted Graph Matching Algorithm
Ravilla Pavithra, Sugantha Priyadharshini. P, I.G. Hemanandhini · 2021
Graph matching (GM) is matching a collection of edges that has no common vertices in a graph. It is an essential problem in computer vision, biosciences, information technology, distributed control and facility allocation and has an important role in solving correspondence problems. Here, optimal graph matching problem for real time DNA datasets are considered. The Weighted Graph Matching and Maximum Weighted Graph Matching algorithms are used for deciding the optimal matching between two weighted graphs. Our work uses an analytic approach to optimize matching problem. The images are converted to adjacency matrices and by computing the Eigen decompositions of the adjacency matrices in case of undirected graphs or Hermitian matrices in case of directed graphs, a matching nearer to the best solution can be obtained once the graphs are satisfactorily nearer to one another.