Robust object matching using a modified version of the hausdorff measure

Yaming Wang, George Baciu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

2 Citations (Scopus)

Abstract

The Hausdorff distance (HD) between planar sets of points is known to be an effective measure for determining the degree of resemblance between binary images. In this paper, we analyze the conventional HD measure and propose a new Robust HD (RHD) measure. The proposed RHD measure takes into account not only the location information of the edge points, but also other factors such as the total number of the edge points whose nearest neighbors are within a specified directed distance, spurious edge segments defined by a small number of points, outliers, and occlusions. Experimental results for both synthetic and real images show that the proposed RHD measure is more efficient than the conventional HD measure.

Original languageEnglish
Pages (from-to)361-373
Number of pages13
JournalInternational Journal of Image and Graphics
Volume2
Issue number3
DOIs
Publication statusPublished - 1 Jul 2002

Keywords

  • Computer Vision
  • Hausdorff Distance
  • Object Matching
  • Occlusion

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design

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