Harmonizing real time data using maximum weighted graph matching

Authors

  • R.Pavithra PG Scholar, Department of Computer Science and Engineering, Coimbatore Institute Of Technology, Coimbatore
  • Dr.R.Prabhakar Professor, Department of Computer Science and Engineering, Coimbatore Institute of Technology, Coimbatore.

Keywords:

Graph Matching, Weighted graph matching algorithm, modified frank-Wolfe, frank Wolfe algorithm.

Abstract

Graph matching is a fundamental problem that arises frequently in the areas of distributed control, computer
vision, and facility allocation. In this paper, we consider the optimal graph matching problem for real time dataset like
fish, house, and bird. Weighted graph matching algorithm is efficient for large number of dataset. The WGMP is the
problem of finding the optimum matching between two weighted graphs, which are graphs with weights at each arc. The
proposed method employs an analytic, instead of a combinatorial or iterative, approach to the optimum matching
problem of such graphs. By using the eigendecompositions of the adjacency matrices (in the case of the undirected graph
matching problem) or some Hermitian matrices derived from the adjacency matrices (in the case of the directed graph
matching problem), a matching close to the optimum one can be found efficiently when the graphs are sufficiently close
to each other. Simulation experiments are also given to evaluate the performance of the proposed method.

Published

2017-04-25

How to Cite

R.Pavithra, & Dr.R.Prabhakar. (2017). Harmonizing real time data using maximum weighted graph matching. International Journal of Advance Engineering and Research Development (IJAERD), 4(4), 969–976. Retrieved from https://ijaerd.com/index.php/IJAERD/article/view/2746