Abstract
A linear programming (LP) approach is proposed for the weighted graph matching problem. A linear program is obtained by formulating the graph matching problem in L1 norm and then transforming the resulting quadratic optimization problem to a linear one. The linear program is solved using a Simplex-based algorithm. Then, approximate 0–1 integer solutions are obtained by applying the Hungarian method on the real solutions of the linear program. The complexity of the proposed algorithm is polynomial time, and it is O(n6L) for matching graphs of size n. The developed algorithm is compared to two other algorithms. One is based on an eigendecomposition approach and the other on a symmetric polynomial transform. Experimental results showed that the LP approach is superior in matching graphs than both other methods.
| Original language | English |
|---|---|
| Pages (from-to) | 522-525 |
| Number of pages | 4 |
| Journal | IEEE Transactions on Pattern Analysis and Machine Intelligence |
| Volume | 15 |
| Issue number | 5 |
| DOIs | |
| State | Published - May 1993 |
Keywords
- Graph matching
- Hungarian method
- linear programming
- optimization
- recognition
- structural pattern
ASJC Scopus subject areas
- Software
- Computer Vision and Pattern Recognition
- Computational Theory and Mathematics
- Artificial Intelligence
- Applied Mathematics