Dempster-Shafer's Basic Probability Assignment Based on Fuzzy Membership Functions

Authors

  • Abdel-Ouahab Boudraa
  • Ayachi Bentabet
  • Fabien Salzenstein

Abstract

In this paper, an image segmentation method based on Dempster-Shafer evidence theory is proposed. Basic probability assignment (bpa) is estimated in unsupervised way using pixels fuzzy membership degrees derived from image histogram. No assumption is made about the images data distribution. bpa is estimated at pixel level. The effectiveness of the method is demonstrated on synthetic and real images.¡

Keywords

image segmentation and image extraction, Data fusion, Basic probability assignment, Demspter-Shafer evidence

DOI

https://doi.org/10.5565/rev/elcvia.68

Published

2004-04-16

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Copyright (c) 2004 Abdel-Ouahab Boudraa, Ayachi Bentabet, Fabien Salzenstein

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.