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Proceedings ArticleDOI

A modified Hausdorff distance for object matching

M.-P. Dubuisson, +1 more
- Vol. 1, pp 566-568
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TLDR
Based on experiments on synthetic images containing various levels of noise, the authors determined that one of these distance measures, called the modified Hausdorff distance (MHD) has the best performance for object matching.
Abstract
The purpose of object matching is to decide the similarity between two objects. This paper introduces 24 possible distance measures based on the Hausdorff distance between two point sets. These measures can be used to match two sets of edge points extracted from any two objects. Based on experiments on synthetic images containing various levels of noise, the authors determined that one of these distance measures, called the modified Hausdorff distance (MHD) has the best performance for object matching. The advantages of MHD ever other distances are also demonstrated on several edge snaps of objects extracted from real images.

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Citations
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Interactive image segmentation using geodesic appearance overlap graph cut

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Learning feature distance measures for image correspondences

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References
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Journal ArticleDOI

Comparing images using the Hausdorff distance

TL;DR: Efficient algorithms for computing the Hausdorff distance between all possible relative positions of a binary image and a model are presented and it is shown that the method extends naturally to the problem of comparing a portion of a model against an image.
Proceedings ArticleDOI

2D matching of 3D moving objects in color outdoor scenes

TL;DR: An object matching system which is able to extract objects of interest from outdoor scenes and match them to obtain a reliable estimate of the average travel time in a road network is described.