A new similarity measure for histogram comparison and its application in time series analysis

Authors:
V. V. Strelkov
Affiliations:
A.M. Prokhorov General Physics Institute of the Russian Academy of Sciences, 38, Vavilov Street, Moscow 119991, Russia
Venue:
Pattern Recognition Letters
Year:
2008

Citing 3
Cited 1

Improving similarity measures of histograms using smoothing projections

Pattern Recognition Letters
Efficient matching of large-size histograms

Pattern Recognition Letters
Signatures versus histograms: Definitions, distances and algorithms

Pattern Recognition

A hierarchical semantic-based distance for nominal histogram comparison

Data & Knowledge Engineering

Quantified Score

Hi-index	0.10

Visualization

Abstract

We suggest a new measure to find similarity between ordered histograms. In our approach the similarity is related to the closeness of positions and shapes of peaks in the compared histograms. Using this measure for comparison of a big number of histograms we obtain results that agree reasonably well with the expert decisions. Applying our peak matching algorithm for studies of the histogram series obtained from experimental data, we reproduce a phenomenon that was found earlier using the expert decisions on the histogram similarity, but was not reproduced with the computer histogram analysis utilized in earlier studies.