Convex shape reconstruction from noisy ray probe measurements

J. S. Lerman, S. R. Kulkarni

Research output: Contribution to conferencePaperpeer-review

1 Scopus citations

Abstract

Two algorithms for two-dimensional convex shape reconstruction from noisy ray probe measurements are developed and compared. Given a coordinate system located within the object, the data consists of a finite set of angles together with the corresponding radial distances to the boundary corrupted by additive noise. We first characterize when such data is consistent with some convex shape. The algorithms estimate the target shape by finding the consistent set of probe measurements that is closest to the original noisy data. A direct formulation leads to a quadratic minimization problem with nonlinear constraints. By applying a simple transformation, an alternative algorithm is developed that trades off performance for computational simplicity as it requires quadratic minimization with linear constraints. Both algorithms are successfully applied to a variety of shapes with substantial noise.

Original languageEnglish (US)
Pages254-257
Number of pages4
StatePublished - Jan 1 1996
Externally publishedYes
EventProceedings of the 1995 IEEE International Conference on Image Processing. Part 3 (of 3) - Washington, DC, USA
Duration: Oct 23 1995Oct 26 1995

Other

OtherProceedings of the 1995 IEEE International Conference on Image Processing. Part 3 (of 3)
CityWashington, DC, USA
Period10/23/9510/26/95

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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