Speeding up Fast Bipartite Graph Matching Through a New Cost Matrix
Francesc Serratosa · International Journal of Pattern Recognition and Artificial Intelligence · 2014
Bipartite (BP) has been seen to be a fast and accurate suboptimal algorithm to solve the Error-Tolerant Graph Matching problem. Recently, Fast Bipartite (FBP) has been presented that obtains the same distance value and node labelings but in a reduced time. Both algorithms approximate the quadratic problem in a linear problem and they do it through a specific cost matrix. FBP imposes the Edit costs to be defined such as the Edit distance is a distance function. Originally, the Hungarian method was used but it has been seen the Jonker–Volgenant linear solver obtains similar results than the Hungarian method but with an important run time reduction. Nevertheless, this second solver has some convergence problems on some specific cost matrices. The aim of this paper is to define a new cost matrix such that the Jonker–Volgenant solver converges and the matching algorithm obtains the same distance value than the BP algorithm.