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The Image Foresting Transform: Theory, Algorithms, and Applications
January 2004 (vol. 26 no. 1)
pp. 19-29

Abstract—The image foresting transform (IFT) is a graph-based approach to the design of image processing operators based on connectivity. It naturally leads to correct and efficient implementations and to a better understanding of how different operators relate to each other. We give here a precise definition of the IFT, and a procedure to compute it—a generalization of Dijkstra's algorithm—with a proof of correctness. We also discuss implementation issues and illustrate the use of the IFT in a few applications.

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Index Terms:
Dijkstra's algorithm, shortest-path problems, image segmentation, image analysis, regional minima, watershed transform, morphological reconstruction, boundary tracking, distance transforms, and multiscale skeletonization.
Citation:
Alexandre X. Falc?, Jorge Stolfi, Roberto de Alencar Lotufo, "The Image Foresting Transform: Theory, Algorithms, and Applications," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 26, no. 1, pp. 19-29, Jan. 2004, doi:10.1109/TPAMI.2004.10012
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