Performance characterization of clustering algorithms for colour image segmentation
Ilea, Dana E. and Whelan, Paul F. and Ghita, Ovidiu (2006) Performance characterization of clustering algorithms for colour image segmentation. In: OPTIM 2006 - 10th International Conference on Optimization of Electrical and Electronic Equipment, 18-19 May 2006, Brasov, Romania.
Full text available as:
This paper details the implementation of three
traditional clustering techniques (K-Means clustering, Fuzzy C-Means clustering and Adaptive K-Means clustering) that are applied to extract the colour information that is used in the image segmentation process. The aim of this paper is to evaluate the performance of the analysed colour clustering techniques for the extraction of optimal features from colour spaces and investigate which method returns the most consistent results when applied on a large suite of mosaic images.
Archive Staff Only: edit this record