Abstract
The Successive Projection Graph Matching (SPGM) algorithm, capable of performing full-and sub-graph matching, is presented in this paper. Projections Onto Convex Sets (POCS) methods have been successfully applied to signal processing applications, image enhancement, neural networks and optics. The SPGM algorithm is unique in the way a constrained cost function is minimized using POCS methodology. Simulation results indicate that the SPGM algorithm compares favorably to other well-known graph matching algorithms.
Cite
CITATION STYLE
van Wyk, B. J., van Wyk, M. A., & Hanrahan, H. E. (2002). Successive projection graph matching. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2396, pp. 263–271). Springer Verlag. https://doi.org/10.1007/3-540-70659-3_27
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