Title :
Two-Dimensional Fuzzy Clustering Algorithm (2DFCM) for Metallographic Image Segmentation Based on Spatial Information
Author :
Lvping Chen ; Yu Han ; Bo Cui ; Yihong Guan ; Yatao Luo
Author_Institution :
Fac. of Sci., Kunming Univ. of Sci. & Technol., Kunming, China
Abstract :
Image segmentation has a positive impact in materials science, and it has application prospect and research value especially in the forecast of material performance. Considering spatial neighbourhood information can improve the accuracy of image segmentation, a novel modified FCM method for image segmentation is presented in this paper. This method take full advantage of the relevance of the current pixel to its neighbour pixels, then design a simple and effective two-dimensional distance metric function, and build a new objective function, so that the cluster centers are updated simultaneously in two dimensions of the pixel value and its neighbouring value. Experiment results of metallographic image segmentation showed that the algorithm has better noise immunity and better convergence rate than the conventional FCM algorithm.
Keywords :
convergence; fuzzy set theory; image resolution; image segmentation; materials science computing; metallography; pattern clustering; 2D distance metric function; 2D fuzzy clustering algorithm method; 2DFCM method; cluster centers; convergence rate; material performance; materials science; metallographic image segmentation; modified FCM method; neighbouring value; noise immunity; pixel value; spatial neighbourhood information; Classification algorithms; Clustering algorithms; Image segmentation; Iron; Noise; Partitioning algorithms; FCM algorithm; image segmentation; metallographic image; the metal material property;
Conference_Titel :
Information Science and Control Engineering (ICISCE), 2015 2nd International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4673-6849-0
DOI :
10.1109/ICISCE.2015.121
