A distance metric for multidimensional histograms.

M. Werman; S. Peleg; A. Rosenfeld

doi:10.1016/0734-189X(85)90055-6

A distance metric for multidimensional histograms.

M. Werman, S. Peleg, A. Rosenfeld

The Rachel and Selim Benin School of Engineering and Computer Science

Research output: Contribution to journal › Article › peer-review

128 Scopus citations

Abstract

A metric is defined on the space of multidimensional histograms. Given two multidimensional histograms, each is 'unfolded' and a minimum distance pairing is performed. The sum of the distances in the minimal pairing is used as the 'match distance' between the histograms. This distance is metric, and in the 1-D case is equal to the absolute difference of the two cumulative distribution functions. It facilitates direct computation of the distance between co-occurrence matrices or between point patterns.-after Authors

Original language	English
Pages (from-to)	328-336
Number of pages	9
Journal	Computer Vision, Graphics, and Image Processing
Volume	32
Issue number	3
DOIs	https://doi.org/10.1016/0734-189X(85)90055-6
State	Published - 1985

Bibliographical note

Funding Information:
*Permanent Address: Dept. of Computer Science, The Hebrew University of Jerusalem, 91904 Jerusalem, Israel. These authors were supported in Israel by a grant from the Israel Academy of Sciences. +The support of the National Science Foundation under grant DCR-82-18408 is gratefully acknowledged, as is the help of Janet Salzman in preparing this paper. 328

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A distance metric for multidimensional histograms.

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