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Title: Window-based method for approximating the Hausdorff in three-dimensional range imagery

Abstract

One approach to pattern recognition is to use a template from a database of objects and match it to a probe image containing the unknown. Accordingly, the Hausdorff distance can be used to measure the similarity of two sets of points. In particular, the Hausdorff can measure the goodness of a match in the presence of occlusion, clutter, and noise. However, existing 3D algorithms for calculating the Hausdorff are computationally intensive, making them impractical for pattern recognition that requires scanning of large databases. The present invention is directed to a new method that can efficiently, in time and memory, compute the Hausdorff for 3D range imagery. The method uses a window-based approach.

Inventors:
 [1]
  1. Albuquerque, NM
Issue Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
963870
Patent Number(s):
7542624
Application Number:
11/238,609
Assignee:
Sandia Corporation (Albuquerque, NM)
Patent Classifications (CPCs):
G - PHYSICS G06 - COMPUTING G06K - RECOGNITION OF DATA
DOE Contract Number:  
AC04-94AL85000
Resource Type:
Patent
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING

Citation Formats

Koch, Mark W. Window-based method for approximating the Hausdorff in three-dimensional range imagery. United States: N. p., 2009. Web.
Koch, Mark W. Window-based method for approximating the Hausdorff in three-dimensional range imagery. United States.
Koch, Mark W. Tue . "Window-based method for approximating the Hausdorff in three-dimensional range imagery". United States. https://www.osti.gov/servlets/purl/963870.
@article{osti_963870,
title = {Window-based method for approximating the Hausdorff in three-dimensional range imagery},
author = {Koch, Mark W},
abstractNote = {One approach to pattern recognition is to use a template from a database of objects and match it to a probe image containing the unknown. Accordingly, the Hausdorff distance can be used to measure the similarity of two sets of points. In particular, the Hausdorff can measure the goodness of a match in the presence of occlusion, clutter, and noise. However, existing 3D algorithms for calculating the Hausdorff are computationally intensive, making them impractical for pattern recognition that requires scanning of large databases. The present invention is directed to a new method that can efficiently, in time and memory, compute the Hausdorff for 3D range imagery. The method uses a window-based approach.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2009},
month = {6}
}

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Works referenced in this record:

A 2D Range Hausdorff Approach for 3D Face Recognition
conference, January 2005


Comparing images using the Hausdorff distance
journal, January 1993

  • Huttenlocher, D. P.; Klanderman, G. A.; Rucklidge, W. J.
  • IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 15, Issue 9
  • https://doi.org/10.1109/34.232073

View-based recognition using an eigenspace approximation to the Hausdorff measure
journal, January 1999

  • Huttenlocher, D. P.; Lilien, R. H.; Olson, C. F.
  • IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 21, Issue 9
  • https://doi.org/10.1109/34.790437