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Performance Evaluation of Image Segmentation

  • Fernando C. Monteiro
  • Aurélio C. Campilho
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4141)

Abstract

In spite of significant advances in image segmentation techniques, evaluation of these methods thus far has been largely subjective. Typically, the effectiveness of a new algorithm is demonstrated only by the presentation of a few segmented images that are evaluated by some method, or it is otherwise left to subjective evaluation by the reader. We propose a new approach for evaluation of segmentation that takes into account not only the accuracy of the boundary localization of the created segments but also the under-segmentation and over-segmentation effects, regardless to the number of regions in each partition. In addition, it takes into account the way humans perceive visual information. This new metric can be applied both to automatically provide a ranking among different segmentation algorithms and to find an optimal set of input parameters of a given algorithm.

Keywords

Ground Truth Image Segmentation Segmentation Algorithm Segmentation Evaluation Segmentation Mask 
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

  • Fernando C. Monteiro
    • 1
    • 2
  • Aurélio C. Campilho
    • 1
    • 3
  1. 1.INEB – Instituto de Engenharia Biomédica 
  2. 2.Escola Superior de Tecnologia e de Gestão de BragançaBragançaPortugal
  3. 3.FEUP – Faculdade de EngenhariaUniversidade do Porto, Rua Dr. Roberto FriasPortoPortugal

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