• DocumentCode
    2748413
  • Title

    Use of fuzzy clustering for determining mass functions Dempster-Shafer theory

  • Author

    Bentabet, Layachi ; ZHU, Yue Min ; Dupuis, Olivier ; KAFTANDJIA, Valérie ; Babot, D. ; ROMBAUT, Michéle

  • Volume
    3
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    1462
  • Abstract
    This paper presents a new approach of automatically determining mass functions in Dempster-Shafer (evidence) theory from the grey levels of images. To achieve this, two underlying aspects have been in particular investigated in the context of segmentation of images from two different sources. The first one concerns the determination of mass function using the fuzzy C-means clustering, and the second one deals with the matching of clusters in the two images being fused. The proposed approach is illustrated with the aid of simulations and examples on physical images
  • Keywords
    fuzzy set theory; image matching; image segmentation; pattern clustering; sensor fusion; uncertainty handling; Dempster-Shafer theory; data fusion; fuzzy clustering; image matching; image segmentation; mass functions; Data structures; Equations; Fuzzy logic; Fuzzy sets; Histograms; Image segmentation; Length measurement; Measurement uncertainty; Pixel; Robustness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing Proceedings, 2000. WCCC-ICSP 2000. 5th International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    0-7803-5747-7
  • Type

    conf

  • DOI
    10.1109/ICOSP.2000.893377
  • Filename
    893377