Robust Gaussian-base radial kernel fuzzy clustering algorithm for image segmentation

To perform the image segmentation task, in this Letter, a kernel fuzzy C-means algorithm is introduced, strengthened by a robust Gaussian radial basis function kernel based on M-estimators. It is well-known that these kernels consider the squared difference as a similarity measure, which is not robu...

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Vydáno v:	Electronics letters Ročník 55; číslo 15; s. 835 - 837
Hlavní autoři:	Mújica-Vargas, Dante, Carvajal-Gámez, Blanca, Ochoa, Genaro, Rubio, José
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	The Institution of Engineering and Technology 25.07.2019
Témata:	colour images fuzzy set theory Gaussian processes Image and vision processing and display technology image segmentation image segmentation task M‐estimators pattern clustering radial basis function networks robust Gaussian radial basis function kernel robust Gaussian‐base radial kernel fuzzy clustering algorithm robust Gaussian radial basis function kernel image segmentation task pattern clustering image segmentation fuzzy set theory Gaussian processes radial basis function networks colour images robust Gaussian-base radial kernel fuzzy clustering algorithm M-estimators
ISSN:	0013-5194, 1350-911X, 1350-911X
On-line přístup:	Získat plný text
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