Graph cuts in computer vision: Difference between revisions

Revision as of 23:09, 10 October 2016

Revision as of 15:22, 2 March 2017

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{{Wikibooks|Algorithm Implementation|Graphs/Maximum flow/Boykov & Kolmogorov}}

The Boykov-Kolmogorov algorithm <ref>Yuri Boykov, Vladimir Kolmogorov: An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Vision. IEEE Trans. Pattern Anal. Mach. Intell. 26(9): 1124–1137 (2004)</ref> is an efficient way to compute the max-flow for computer vision related graph.

=== Implementation (approximation) ===

The Sim Cut algorithm <ref>P.J. Yim: "Method and System for Image Segmentation," United States Patent US8929636, January 6, 2016 </ref> approximates the graph cut by the solution of the set of simultaneous non-linear equations based on the analog electrical model of the flow network.<ref> I.T. Frisch, "On Electrical analogs for flow networks," Proceedings of IEEE, 57:2, pp. 209-210, 1969 </ref> Acceleration of the algorithm is possible through parallel computing.

== Software ==