This paper describes a new approach to geometrically guided fuzzy clustering. A modified version of fuzzy C-means (FCM) clustering, conditional FCM, is extended to incorporate a priori geometrical information from the spatial domain in order to improve image segmentation. This leads to a new algorithm (GGC-FCM) where the cluster guidance is determined by the membership values of neighbouring pixels. GGC-FCM is tested on synthetic and real images to demonstrate the improved image segmentation compared to traditional FCM. Copyright (C) 2002 John Wiley Sons, Ltd.
- Multivariate imaging
- Multispectral imaging
Noordam, J. C., & van den Broek, W. H. A. M. (2002). Multivariate image segmentation based on geometrically guided fuzzy C-means clustering. Journal of Chemometrics, 16(1), 1-11. https://doi.org/10.1002/cem.656