Abstract
We present an image segmentation approach which is invariant to affine transformation – the result after rescaling the picture remains almost the same as before. Moreover, the algorithm detects automatically the correct number of groups. We show that the method is capable of discovering general shapes as well as small details by the appropriate choice of only two input parameters.
This research was supported by National Centre of Science (Poland) Grants No. 2011/01/B/ST6/01887.
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© 2013 Springer International Publishing Switzerland
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Śmieja, M., Tabor, J. (2013). Image Segmentation with Use of Cross-Entropy Clustering. In: Burduk, R., Jackowski, K., Kurzynski, M., Wozniak, M., Zolnierek, A. (eds) Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013. Advances in Intelligent Systems and Computing, vol 226. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00969-8_39
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DOI: https://doi.org/10.1007/978-3-319-00969-8_39
Publisher Name: Springer, Heidelberg
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