The Earth Mover's Distance as a Metric for Image Retrieval
International Journal of Computer Vision
Efficient matching of large-size histograms
Pattern Recognition Letters
Signatures versus histograms: Definitions, distances and algorithms
Pattern Recognition
A new algorithm to compute the distance between multi-dimensional histograms
CIARP'07 Proceedings of the Congress on pattern recognition 12th Iberoamerican conference on Progress in pattern recognition, image analysis and applications
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The aim of this paper is to present an efficient distance between n-dimensional histograms. Some image classification or image retrieval techniques use the distance between histograms as a first step of the classification process. For this reason, some algorithms that find the distance between histograms have been proposed in the literature. Nevertheless, most of this research has been applied on one-dimensional histograms due to the computation of a distance between multi-dimensional histograms is very expensive. In this paper, we present an efficient method to compare multi-dimensional histograms in O(2z), where z represents the number of bins. Results show a huge reduction of the time consuming with no recognition-ratio reduction.