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PVLDB

2011

2011

The Hausdorff distance is commonly used as a similarity measure between two point sets. Using this measure, a set X is considered similar to Y iff every point in X is close to at least one point in Y . Formally, the Hausdorff distance HAUSDIST(X, Y ) can be computed as the MAX-MIN distance from X to Y , i.e., ﬁnd the maximum of the distance from an element in X to its nearest neighbor (NN) in Y . Although this is similar to the closest pair and farthest pair problems, computing the Hausdorff distance is a more challenging problem since its MAX-MIN nature involves both maximization and minimization rather than just one or the other. A traditional approach to computing HAUSDIST(X, Y ) performs a linear scan over X and utilizes an index to help compute the NN in Y for each x in X. We present a pair of basic solutions that avoid scanning X by applying the concept of aggregate NN search to searching for the element in X that yields the Hausdorff distance. In addition, we propose a novel ...

Related Content

Added |
17 Sep 2011 |

Updated |
17 Sep 2011 |

Type |
Journal |

Year |
2011 |

Where |
PVLDB |

Authors |
Sarana Nutanong, Edwin H. Jacox, Hanan Samet |

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