Iota (sub 1) and Iota (sub infinity) ODR Fitting of Geometric Elements

Abstract

We consider the fitting of geometric elements, such as lines, planes, circles, cones, and cylinders, in such a way that the sum of distances or the maximal distance from the element to the data points is minimized. We refer to this kind of distance based fitting as orthogonal distance regression or ODR. We present a separation of variables algorithm for iota(sub 1) and iota(sub infinity) ODR fitting of geometric elements. The algorithm is iterative and allows the element to be given in either implicit form f(chi, beta) = 0 or in parametric form chi = g(t, Beta) where Beta is the vector of shape parameters, chi is a 2- or 3-vector, and s is a vector of location parameters. The algorithm may even be applied in cases, such as with ellipses, in which a closed form expression for the distance is either not available or is difficult to compute. For iota(sub 1) and iota (sub infinity) fitting, the norm of the gradient is not available as a stopping criterion, as it is not continuous. We present a stopping criterion that handles both the iota(sub 1) and the iota(sub infinity) case, and is based on a suitable characterization of the stationary points.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 2001
Accession Number
ADP013727

Entities

People

  • Daniel S. Zwick
  • Hans-peter Helfrich

Organizations

  • University of Bonn

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Continuity
  • Convergence
  • Data Sets
  • Iterations
  • Linear Programming
  • Scalar Functions
  • Sequences
  • Symposia
  • Technical Information Centers

Readers

  • Approximation Theory.
  • Linear Algebra
  • Statistical inference.