Abstract
It is presented a new type of learning textures recognition algorithms based on serial statistical tests. It is assumed that a texture can be formally represented by a multi-component random vector whose probabilistic characteristics are, in general, a priori unknown. Discrimination of textures is equivalent to a discrimination of random vectors of different but a priori unknown statistical properties. For this purpose non-parametric statistical tests based on serial statistics are used. Construction of serial statistics needs a linear ordering of multi-dimensional observation space. The method is illustrated by numerical examples.
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References
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© 2005 Springer-Verlag Berlin Heidelberg
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Kulikowski, J.L., Przytulska, M., Wierzbicka, D. (2005). A Method of Supervised Discrimination of Textures Based on Serial Statistical Tests. In: Kurzyński, M., Puchała, E., Woźniak, M., żołnierek, A. (eds) Computer Recognition Systems. Advances in Soft Computing, vol 30. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32390-2_26
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DOI: https://doi.org/10.1007/3-540-32390-2_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25054-8
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