Significantly Fast and Robust Fuzzy C-Means Clustering Algorithm Based on Morphological Reconstruction and Membership Filtering

As fuzzy c-means clustering (FCM) algorithm is sensitive to noise, local spatial information is often introduced to an objective function to improve the robustness of the FCM algorithm for image segmentation. However, the introduction of local spatial information often leads to a high computational...

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Bibliographic Details
Published in:	IEEE transactions on fuzzy systems Vol. 26; no. 5; pp. 3027 - 3041
Main Authors:	Lei, Tao, Jia, Xiaohong, Zhang, Yanning, He, Lifeng, Meng, Hongying, Nandi, Asoke K.
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.10.2018 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Clustering Clustering algorithms Computational complexity Electronic mail Filtration Fuzzy c-means clustering (FCM) Image filters Image reconstruction Image segmentation Immunity Iterative methods Linear programming local spatial information Matrix partitioning morphological reconstruction (MR) Morphology Noise sensitivity Partitioning algorithms Pixels Robustness Spatial data State of the art
ISSN:	1063-6706, 1941-0034
Online Access:	Get full text
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