Abstract
The article describes universal model for creating algorithms for calculating textural image features. The proposed models are used for images that are realizations of Markov Random Field. Experimental classification results are shown for different images sets.
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Plastinin, A. (2011). Regression Models for Texture Image Analysis. In: Kuznetsov, S.O., Mandal, D.P., Kundu, M.K., Pal, S.K. (eds) Pattern Recognition and Machine Intelligence. PReMI 2011. Lecture Notes in Computer Science, vol 6744. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21786-9_24
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DOI: https://doi.org/10.1007/978-3-642-21786-9_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21785-2
Online ISBN: 978-3-642-21786-9
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