• DocumentCode
    1645670
  • Title

    Image segmentation for appearance-based self-localisation

  • Author

    Zingaretti, P. ; Bossoletti, L.

  • fYear
    2001
  • Firstpage
    113
  • Lastpage
    118
  • Abstract
    The paper describes a segmentation technique that well fits to an appearance-based self-localisation. In an appearance-based approach robot positioning is performed without using explicit object models. The choice of the representation of image appearances is fundamental. We use image-domain features, as opposed to interpreted characteristics of the scene, and we adopt feature vectors including both the chromatic attributes of colour sets and their mutual spatial relationships. To obtain the colour sets we perform image segmentation by autothresholding the colour histograms and taking into account what the results are addressed to. The experimental results indicate that the method performs well for a variety of environments
  • Keywords
    feature extraction; image colour analysis; image representation; image segmentation; robot vision; statistical analysis; appearance-based self-localisation; autothresholding; chromatic attributes; colour histograms; colour sets; feature vectors; image representation; image segmentation; image-domain features; robot positioning; spatial relationship; Data mining; Feature extraction; Histograms; Image segmentation; Layout; Mobile robots; Navigation; Path planning; Robot sensing systems; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Analysis and Processing, 2001. Proceedings. 11th International Conference on
  • Conference_Location
    Palermo
  • Print_ISBN
    0-7695-1183-X
  • Type

    conf

  • DOI
    10.1109/ICIAP.2001.956994
  • Filename
    956994