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| H.A. Almohamad, S.O. Duffuaa, "A Linear Programming Approach for the Weighted Graph Matching Problem," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 15, no. 5, pp. 522-525, May, 1993. | |||
| BibTex | x | ||
| @article{ 10.1109/34.211474, author = {H.A. Almohamad and S.O. Duffuaa}, title = {A Linear Programming Approach for the Weighted Graph Matching Problem}, journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {15}, number = {5}, issn = {0162-8828}, year = {1993}, pages = {522-525}, doi = {http://doi.ieeecomputersociety.org/10.1109/34.211474}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - JOUR JO - IEEE Transactions on Pattern Analysis and Machine Intelligence TI - A Linear Programming Approach for the Weighted Graph Matching Problem IS - 5 SN - 0162-8828 SP522 EP525 EPD - 522-525 A1 - H.A. Almohamad, A1 - S.O. Duffuaa, PY - 1993 KW - computational complexity; linear programming; weighted graph matching; quadratic optimization; simplex-based algorithm; Hungarian method; polynomial time; eigendecomposition; symmetric polynomial transform; computational complexity; linear programming; pattern recognition VL - 15 JA - IEEE Transactions on Pattern Analysis and Machine Intelligence ER - | |||
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 L/sub 1/ 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(n/sup 6/L) 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.
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