A New Algorithm to Compute the Distance Between Multi-dimensional Histograms
The aim of this paper is to present a new algorithm to compute the distance between n-dimensional histograms. There are some domains such as pattern recognition or image retrieval that use the distance between histograms at some 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(z 2 ), where z represents the number of bins.
KeywordsMulti-dimensional Histogram distance Earth Movers Distance Second-Order Random Graphs
- 3.Numerical Recipes in C: The Art of Scientific Computing, ISBN 0-521-43108-5. Google Scholar
- 9.Chapelle, O., Haffner, P., Vapnik, V.N.: Support Vector Machines for Histogram-Based Image Classification. IEEE Trans. On Neural Net. (10) (1999)Google Scholar
- 10.Gong, Y., Chuan, C.H., Xiaoyi, G.: Image indexing and retrieval based on colour histograms. Multimedia Tools and Applications 2(2), 133–156 (1996)Google Scholar
- 11.Serratosa, F., Sanromà, G.: An Efficient Distance between Multi-dimensional Histograms for Comparing images. In: SSPR 2006. LNCS (2006)Google Scholar