• DocumentCode
    2039646
  • Title

    Strategy for shape-based image analysis

  • Author

    Reinhardt, Joseph M. ; Higgins, William E.

  • Author_Institution
    Coll. of Med., Iowa Univ., Iowa City, IA, USA
  • Volume
    1
  • fYear
    1995
  • fDate
    23-26 Oct 1995
  • Firstpage
    502
  • Abstract
    Traditional image segmentation methods typically divide an image into separate regions based on the grayscale characteristics of the image. For most real-world image-segmentation problems, however, these methods tend to produce imperfectly shaped regions that require some degree of shape modification to yield acceptable results. Choosing an appropriate sequence of operators and associated operator parameters, though, is a tedious procedure and requires much image-processing expertise. We describe a strategy for easily selecting shape-based operations. Shape information on regions in an image is provided by the user in the form of easily-specified cues. The user is not required to be an image-processing expert to apply the strategy-he need only be able to specify the desired shape properties of the regions in the image
  • Keywords
    image segmentation; grayscale characteristics; image processing; image regions; image segmentation methods; operator parameters; shape based image analysis; shape based operation selection; shape information; shape modification; shape properties; Biomedical imaging; Cities and towns; Educational institutions; Gray-scale; Image analysis; Image segmentation; Image sequence analysis; Radiology; Shape; Topology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 1995. Proceedings., International Conference on
  • Conference_Location
    Washington, DC
  • Print_ISBN
    0-8186-7310-9
  • Type

    conf

  • DOI
    10.1109/ICIP.1995.529756
  • Filename
    529756