An automatic fuzzy clustering segmentation algorithm with aid of set partitioning
Yanling Li, Zhiwei Gao, Xiaoxu Liu · 2017
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.