International Journal of Computer Vision

, Volume 59, Issue 2, pp 167–181 | Cite as

Efficient Graph-Based Image Segmentation

  • Pedro F. Felzenszwalb
  • Daniel P. Huttenlocher

Abstract

This paper addresses the problem of segmenting an image into regions. We define a predicate for measuring the evidence for a boundary between two regions using a graph-based representation of the image. We then develop an efficient segmentation algorithm based on this predicate, and show that although this algorithm makes greedy decisions it produces segmentations that satisfy global properties. We apply the algorithm to image segmentation using two different kinds of local neighborhoods in constructing the graph, and illustrate the results with both real and synthetic images. The algorithm runs in time nearly linear in the number of graph edges and is also fast in practice. An important characteristic of the method is its ability to preserve detail in low-variability image regions while ignoring detail in high-variability regions.

image segmentation clustering perceptual organization graph algorithm 

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Copyright information

© Kluwer Academic Publishers 2004

Authors and Affiliations

  • Pedro F. Felzenszwalb
    • 1
  • Daniel P. Huttenlocher
    • 2
  1. 1.Artificial Intelligence LabMassachusetts Institute of TechnologyUSA
  2. 2.Computer Science DepartmentCornell UniversityUSA

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