Abstract
Fuzzy C-means clustering algorithm is a classical non-supervised classification method. For image classification, fuzzy C-means clustering algorithm makes decisions on a pixel-by-pixel basis and does not take advantage of spatial information, regardless of the pixels’ correlation. In this letter, a novel fuzzy C-means clustering algorithm is introduced, which is based on image’s neighborhood system. During classification procedure, the novel algorithm regards all pixels’ fuzzy membership as a random field. The neighboring pixels’ fuzzy membership information is used for the algorithm’s iteration procedure. As a result, the algorithm gives a more smooth classification result and cuts down the computation time.
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Huang, N., Zhu, M. & Zhang, S. Considering neighborhood information in image fuzzy clustering. J. of Electron.(China) 19, 307–310 (2002). https://doi.org/10.1007/s11767-002-0056-5
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DOI: https://doi.org/10.1007/s11767-002-0056-5