Abstract
The paper proposes a new method to approximate the normalized information distance by a compression method that is particularly suited for image data. The new method is based on a video compressor. The new method is used to compute the distance matrix of all the images in the data sets considered. Moreover, the hierarchical clustering method from the R package is used to cluster the distance matrix obtained. Two different datasets are considered to demonstrate the usefulness of our new image analysis method. The results are very promising and show that one can obtain a very good clustering of the image data.
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We would like to thank to the program committee and the anonymous referees for their valuable comments.
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Zhu, Y., Zeugmann, T. (2016). Image Analysis in a Parameter-Free Setting. In: Abdelrahman, O., Gelenbe, E., Gorbil, G., Lent, R. (eds) Information Sciences and Systems 2015. Lecture Notes in Electrical Engineering, vol 363. Springer, Cham. https://doi.org/10.1007/978-3-319-22635-4_26
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DOI: https://doi.org/10.1007/978-3-319-22635-4_26
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