Abstract
There are many different approaches to measure dissimilarities between images on the basis of color histograms. Some of them operate fast but generate results in contradiction to human perception. Others yield better results, especially the Earth Mover’s Distance (EMD) (Rubner et al., Int J Comput Vis, 40(2): 99–121, 2000), but its computational complexity prevents its usage in large databases (Ling et al., IEEE Trans Pattern Anal Mach Intell, 29(5):840–853, 2007). This paper presents a new intuitive intelligible approximation of EMD. The empirical study tries to answer the question whether the good results of EMD justify its long computation time. We tested several distances with images that were changed by normally-distributed failures and evaluate their results by means of the adjusted Rand index (Hubert et al., J Classif, 2:193–218, 1985).
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This research is funded by Federal Ministry for Education and Research under grants 03FO3072. The author is responsible for the content of this paper.
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Frost, S., Baier, D. (2013). Comparing Earth Mover’s Distance and its Approximations for Clustering Images. In: Lausen, B., Van den Poel, D., Ultsch, A. (eds) Algorithms from and for Nature and Life. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Cham. https://doi.org/10.1007/978-3-319-00035-0_6
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DOI: https://doi.org/10.1007/978-3-319-00035-0_6
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