Robust detection of road segments in noisy aerial images

Nathan S. Netanyahu, Vasanth Philomin, Azriel Rosenfeld, Arnold J. Stromberg

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations


This paper treats the problem of detecting straight or circular pieces of road in noisy aerial images. It first uses a local nonlinear operator to detect pixels whose neighborhoods are line-like, and then applies (robust) estimation techniques to find sets of such pixels that lie on, or near straight or circular loci. An (unbiased) ordinary least squares estimator cannot handle outlying data; on the other hand, conventional robust techniques for fitting circular arcs are severely affected by digitization effects and the fact that road circular segments are typically short and shallow. We therefore introduce an estimator that is both robust and statistically efficient.

Original languageEnglish
Title of host publicationTrack B
Subtitle of host publicationPattern Recognition and Signal Analysis
Number of pages5
StatePublished - 1996
Event13th International Conference on Pattern Recognition, ICPR 1996 - Vienna, Austria
Duration: Aug 25 1996Aug 29 1996

Publication series

NameProceedings - International Conference on Pattern Recognition
ISSN (Print)1051-4651


Conference13th International Conference on Pattern Recognition, ICPR 1996


  • circular arc fitting
  • Line fitting
  • nonlinear regression
  • ordinary least squares
  • robust estimators

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition


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