• DocumentCode
    177776
  • Title

    Spatially-Variant Area Openings for Reference-Driven Adaptive Contour Preserving Filtering

  • Author

    Franchi, G. ; Angulo, J.

  • Author_Institution
    CMM-Centre de Morphologie Math., MINES ParisTech, Paris, France
  • fYear
    2014
  • fDate
    24-28 Aug. 2014
  • Firstpage
    1043
  • Lastpage
    1048
  • Abstract
    Classical adaptive mathematical morphology is based on operators which locally adapt the structuring elements to the image properties. Connected morphological operators act on the level of the flat zones of an image, such that only flat zones are filtered out, and hence the object edges are preserved. Area opening (resp. area closing) is one of the most useful connected operators, which filters out the bright (resp. dark) regions. It intrinsically involves the adaptation of the shape of the structuring element parameterized by its area. In this paper, we introduce the notion of reference-driven adaptive area opening according to two spatially-variant paradigms. First, the parameter of area is locally adapted by the reference image. This approach is applied to processing intensity depth images where the depth image is used to adapt the scale-size processing. Second, a self-dual area opening, where the reference image determines if the area filter is an opening or a closing with respect to the relationship between the image and the reference. Its natural application domain are the video sequences.
  • Keywords
    edge detection; filtering theory; image sequences; mathematical morphology; video signal processing; classical adaptive mathematical morphology; connected operators; image properties; morphological operators; object edges; reference driven adaptive contour preserving filtering; scale-size processing; spatially variant area openings; spatially variant paradigms; video sequences; Area measurement; Boolean functions; Cameras; Level set; Morphology; Shape; Transforms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition (ICPR), 2014 22nd International Conference on
  • Conference_Location
    Stockholm
  • ISSN
    1051-4651
  • Type

    conf

  • DOI
    10.1109/ICPR.2014.189
  • Filename
    6976899