Straight edge extraction and matching

Yuncai Liu, Thomas S. Huang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents an algorithm for straight edge extraction from intensity images and an algorithm for straight line matching. In the first part of the paper, straight edge extraction is described. Image data are first processed by the operation of edge support focusing to remove unnecessary image details. An edge support is formed in this process. Then, straight edges are extracted from line support regions, which are segmented from the edge support. In second part of this paper, we describe straight line matching using a matching function, which characterizes the similarity of edge lines of two images and is based on not only the geometrical relations of the lines but also the information from the intensity images. A technique of kernel matching is applied to reduce the cost of computation. The motivation behind this paper is our work on motion estimation from line correspondences of sequential images where straight edge extraction and matching is an essential first step. The output data of the algorithm can also be used for calibration of stereo camera setups. The results of experiments using indoor and outdoor scene images are shown.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
EditorsA. Gruen, E. Baltsavias
PublisherPubl by Int Soc for Optical Engineering
Pages612-619
Number of pages8
Editionpt 1
ISBN (Print)0819404411
StatePublished - Dec 1 1990
EventClose-Range Photogrammetry Meets Machine Vision - Zurich, Switz
Duration: Sep 3 1990Sep 7 1990

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Numberpt 1
Volume1395
ISSN (Print)0277-786X

Other

OtherClose-Range Photogrammetry Meets Machine Vision
CityZurich, Switz
Period9/3/909/7/90

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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