• DocumentCode
    394057
  • Title

    A statistical analysis of shape reconstruction from areas of shadows

  • Author

    Poonawala, Amyn ; Milanfar, Peyman ; Gardner, Richard J.

  • Author_Institution
    Dept. of Comput. Eng., California Univ., Santa Cruz, CA, USA
  • Volume
    1
  • fYear
    2002
  • fDate
    3-6 Nov. 2002
  • Firstpage
    916
  • Abstract
    We present a statistical analysis of the problem of shape reconstruction from measurements of the brightness function (areas of shadows) by deriving the Cramer-Rao lower bound (CRLB) on the estimated 2-D boundary. Confidence region techniques are used to analyze and visualize the performance of the 2-D parametric shape estimation problem. The brightness function data is very weak, so a constrained CRLB is used on the shape parameters to form the confidence regions. Algorithms for reconstructing the shape of a convex object from multiple measurements of its brightness function were developed in [R. J. Gardner and P. Milanfar, "Shape reconstruction from brightness functions", August 2001] and [R. J. Gardner and P. Milanfar, "Reconstruction of convex bodies from brightness functions"]. The Cramer-Rao bound analysis presented provides statistical estimates that can be used for performance evaluation of these algorithms.
  • Keywords
    brightness; image reconstruction; inverse problems; parameter estimation; statistical analysis; CRLB; Cramer-Rao lower bound; brightness function data; brightness function measurement; confidence region technique; eccentricity; parametric shape estimation problem; shadow areas; shape reconstruction; statistical analysis; Algorithm design and analysis; Area measurement; Brightness; Data visualization; Electric variables measurement; Image reconstruction; Performance analysis; Shape measurement; Statistical analysis; Tomography;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signals, Systems and Computers, 2002. Conference Record of the Thirty-Sixth Asilomar Conference on
  • Conference_Location
    Pacific Grove, CA, USA
  • ISSN
    1058-6393
  • Print_ISBN
    0-7803-7576-9
  • Type

    conf

  • DOI
    10.1109/ACSSC.2002.1197310
  • Filename
    1197310