caa a22 4500 605470782 CHVBK 20210128100329.0 cr unu---uuuuu 210128e20151101xx s 000 0 eng 10.1007/s00500-014-1481-8 doi (NATIONALLICENCE)springer-10.1007/s00500-014-1481-8 A modified strategy of fuzzy clustering algorithm for image segmentation [Elektronische Daten] [Dongguo Zhou, Hong Zhou] Fuzzy clustering algorithm is a frequently used method for image segmentation, which allows pixel to be classified into one or more clusters with respect to its membership level. However, its segmentation performance often suffered from the factors associated with the drift of cluster centers and the sensitiveness to the intensity overlap of distribution between classes. In this paper, we solve these drawbacks and present a modified strategy of fuzzy clustering algorithm for image segmentation. This strategy generally consists of two-pass processes. The first process is to directly calculate the cluster centers from the segmented image and then take the higher value of cluster centers as an alternative threshold to prevent the pixels with lower intensity from clustering. The second process thereby makes use of the fuzzy clustering algorithm with a bias field for partitioning pixels with spatial proximity, ensuring that our method is less sensitive to the drawbacks inherent in the fuzzy clustering algorithm and thus obtaining promising results. Experiments on synthetic and some representative infrared images demonstrate that the proposed method outperforms fuzzy c-means methods and its existing variants in terms of segmentation performance, and is less sensitive to the intensity overlap of the distribution between classes. Springer-Verlag Berlin Heidelberg, 2014 Image segmentation nationallicence Infrared image nationallicence Fuzzy clustering algorithm nationallicence Cluster center nationallicence Zhou Dongguo School of Power and Mechanical Engineering, Wuhan University, 430072, Wuhan, China aut Zhou Hong School of Power and Mechanical Engineering, Wuhan University, 430072, Wuhan, China aut Soft Computing Springer Berlin Heidelberg 19/11(2015-11-01), 3261-3272 1432-7643 19:11<3261 2015 19 500 https://doi.org/10.1007/s00500-014-1481-8 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00500-014-1481-8 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Zhou Dongguo School of Power and Mechanical Engineering, Wuhan University, 430072, Wuhan, China aut NATIONALLICENCE 700 1- Zhou Hong School of Power and Mechanical Engineering, Wuhan University, 430072, Wuhan, China aut NATIONALLICENCE 773 0- Soft Computing Springer Berlin Heidelberg 19/11(2015-11-01), 3261-3272 1432-7643 19:11<3261 2015 19 500