• Title of article

    A comparison of least-squares and Bayesian minimum risk edge parameter estimation

  • Author/Authors

    Mulder، Nanno J. نويسنده , , Abkar، Ali A. نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 1999
  • Pages
    -1396
  • From page
    1397
  • To page
    0
  • Abstract
    Atesselation (sigma) is called strongly normal, if it is normal (topological discs with intersections that are either empty or connected) and for any subset of cells C1.....,C(K), C* of the tesselation holds: if the intersection (intersection k i=1) C(i), of all C(i), is nonempty and each C, has nonempty intersection with C*, then the intersection C* intersection intersection k i=1) C(i), of all C, with C* is nonempty. This concept was introduced for polygonal or polyhedral cells in a recent paper by Saha and Rosenfeld, where they proved that it is equivalent to the topological property that any cell together with any set of neighbouring cells forms a simply connected set. Answering a question from their paper, it is shown here that at least in the plane the cells need not be convex polygons, but can be arbitrary topological discs. Also the property is already implied if all collections of three cells have this property, giving a simpler characterization and a connection to Helly-type theorems.
  • Keywords
    Edge detection , parameter estimation , Least squares , Likelihood , Remote sensing
  • Journal title
    PATTERN RECOGNITION LETTERS
  • Serial Year
    1999
  • Journal title
    PATTERN RECOGNITION LETTERS
  • Record number

    14936