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Fast fuzzy clustering of infrared images
Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569)
Clustering is an important technique for unsupervised image segmentation. The use of fuzzy c-means clustering can provide more information and better partitions than traditional c-means. In image processing, the ability to reduce the precision of the input data and aggregate similar examples can lead to significant data reduction and correspondingly less execution time. This paper discusses brFCM, a data reduction fuzzy c-means clustering algorithm. The algorithm is described and several key
doi:10.1109/nafips.2001.944766
fatcat:42tbabhbffdcbjzlt4jxfqcul4