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Image Specific Feature Similarities

  • Ido Omer
  • Michael Werman
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3952)

Abstract

Calculating a reliable similarity measure between pixel features is essential for many computer vision and image processing applications. We propose a similarity measure (affinity) between pixel features, which depends on the feature space histogram of the image. We use the observation that clusters in the feature space histogram are typically smooth and roughly convex. Given two feature points we adjust their similarity according to the bottleneck in the histogram values on the straight line between them. We call our new similarities Bottleneck Affinities. These measures are computed efficiently, we demonstrate superior segmentation results compared to the use of the Euclidean metric.

Keywords

Feature Space Feature Point Image Segmentation Texture Feature Segmentation Result 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Ido Omer
    • 1
  • Michael Werman
    • 1
  1. 1.School of Computer ScienceThe Hebrew University of JerusalemJerusalemIsrael

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