Random walks for image segmentation

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Random walks for image segmentation (2006)

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by Leo Grady

Venue:	IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
Citations:	387 - 21 self

BibTeX

@ARTICLE{Grady06randomwalks,
    author = {Leo Grady},
    title = {Random walks for image segmentation},
    journal = {IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE},
    year = {2006},
    volume = {28},
    number = {11},
    pages = {1768--1778}
}

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Abstract

A novel method is proposed for performing multilabel, interactive image segmentation. Given a small number of pixels with user-defined (or predefined) labels, one can analytically and quickly determine the probability that a random walker starting at each unlabeled pixel will first reach one of the prelabeled pixels. By assigning each pixel to the label for which the greatest probability is calculated, a high-quality image segmentation may be obtained. Theoretical properties of this algorithm are developed along with the corresponding connections to discrete potential theory and electrical circuits. This algorithm is formulated in discrete space (i.e., on a graph) using combinatorial analogues of standard operators and principles from continuous potential theory, allowing it to be applied in arbitrary dimension on arbitrary graphs.

Keyphrases

random walk image segmentation combinatorial analogue standard operator laplace equation boundary completion continuous potential theory potential theory interactive image segmentation unlabeled pixel interactive segmentation theoretical property harmonic function graph cut combinatorial dirichlet problem graph theory discrete space random walker high-quality image segmentation electrical circuit small number arbitrary dimension corresponding connection index term image segmentation prelabeled pixel novel method arbitrary graph

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