@inproceedings{0f7be47644b74637a0c4657f52bddeb8,
title = "An automatic fuzzy clustering segmentation algorithm with aid of set partitioning",
abstract = "As one of the most popular methods for image segmentation, fuzzy C-means algorithm suffers two unavoidable initialization difficulties including obtaining initial cluster centroids and deciding cluster number, which affect the algorithm performance. Motivated by the above, an automatic fuzzy clustering algorithm is proposed in this paper, where observation matrix, judgment matrix and set partitioning are used to select appropriate clustering number automatically. Experimental results show that automatic fuzzy clustering algorithm not only can spontaneously estimate the appropriate number of clusters but also can achieve better segmentation quality.",
keywords = "Fuzzy clustering, image segmentation, observation matrix, set partitioning",
author = "Yanling Li and Zhiwei Gao and Xiaoxu Liu",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE. Copyright: Copyright 2018 Elsevier B.V., All rights reserved.; 15th IEEE International Conference on Industrial Informatics, INDIN 2017 ; Conference date: 24-07-2017 Through 26-07-2017",
year = "2017",
month = nov,
day = "10",
doi = "10.1109/INDIN.2017.8104848",
language = "English",
series = "Proceedings - 2017 IEEE 15th International Conference on Industrial Informatics, INDIN 2017",
publisher = "IEEE",
pages = "647--652",
booktitle = "Proceedings - 2017 IEEE 15th International Conference on Industrial Informatics, INDIN 2017",
address = "United States",
}