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A Weighted Common Subgraph Matching Algorithm
- Publication Year :
- 2014
-
Abstract
- We propose a weighted common subgraph (WCS) matching algorithm to find the most similar subgraphs in two labeled weighted graphs. WCS matching, as a natural generalization of the equal-sized graph matching or subgraph matching, finds wide applications in many computer vision and machine learning tasks. In this paper, the WCS matching is first formulated as a combinatorial optimization problem over the set of partial permutation matrices. Then it is approximately solved by a recently proposed combinatorial optimization framework - Graduated NonConvexity and Concavity Procedure (GNCCP). Experimental comparisons on both synthetic graphs and real world images validate its robustness against noise level, problem size, outlier number, and edge density.<br />Comment: 6 pages, 5 figures, the second round revision in IEEE TNNLS
Details
- Database :
- arXiv
- Publication Type :
- Report
- Accession number :
- edsarx.1411.0763
- Document Type :
- Working Paper