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

• Autores: Abdel-Ouahab Boudraa, Ayachi Bentabet, Fabien Salzenstein, Laurent Guillon
• Localización: ELCVIA. Electronic letters on computer vision and image analysis, ISSN-e 1577-5097, Vol. 4, Nº. 1, 2004, págs. 1-10
• Idioma: inglés
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• Resumen

  • 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.