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:
-
- 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)
- 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 = {Tue Jun 02 00:00:00 EDT 2009},
month = {Tue Jun 02 00:00:00 EDT 2009}
}
Works referenced in this record:
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conference, January 2005
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Comparing images using the Hausdorff distance
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View-based recognition using an eigenspace approximation to the Hausdorff measure
journal, January 1999
- Huttenlocher, D. P.; Lilien, R. H.; Olson, C. F.
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