The image foresting transform: Theory, algorithms, and applications

被引：391

作者：

Falcao, AX

Stolfi, J

Lotufo, RDA

机构：

[1] Univ Estadual Campinas, Inst Comp, BR-13084851 Campinas, SP, Brazil

[2] Univ Estadual Campinas, Fac Elect & Comp Engn, BR-13083970 Campinas, SP, Brazil

来源：

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE | 2004年 / 26卷 / 01期

关键词：

Dijkstra's algorithm; shortest-path problems; image segmentation; image analysis; regional minima; watershed transform; morphological reconstruction; boundary tracking; distance transforms; and multiscale skeletonization;

D O I：

10.1109/TPAMI.2004.1261076

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：19 / 29

页数：11

共 52 条

[31] Fuzzy-connected 3D image segmentation at interactive speeds [J].