Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/32060
Title: Robust object matching using a modified version of the hausdorff measure
Authors: Wang, Y
Baciu, G 
Keywords: Hausdorff Distance
Computer Vision
Object Matching
Occlusion
Issue Date: 2002
Publisher: World Scientific
Source: International journal of image and graphics, 2002, v. 2, no. 3, p. 361-373 How to cite?
Journal: International journal of image and graphics 
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.
URI: http://hdl.handle.net/10397/32060
ISSN: 0219-4678
EISSN: 1793-6756
DOI: 10.1142/S0219467802000688
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page view(s)

45
Last Week
4
Last month
Checked on Nov 19, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.