Title :
Cluster-based segmentation of natural scenes
Author :
Pauwels, Eric J. ; Frederix, Greet
Author_Institution :
ESAT-PSI, Katholieke Univ., Leuven, Belgium
Abstract :
In cluster-based segmentation pixels are mapped into various feature spaces whereupon they are subjected to a grouping algorithm. In this paper we develop a robust and versatile non-parametric clustering algorithm that is able to handle the unbalanced and irregular clusters encountered in such segmentation applications. The strength of our approach lies in the definition and use of two cluster validity indices that are independent of the cluster topology. By combining them, an excellent clustering can be identified, and experiments confirm that the associated clusters do indeed correspond to perceptually salient image regions
Keywords :
computer vision; content-based retrieval; image segmentation; pattern clustering; cluster topology; cluster validity indices; cluster-based segmentation; feature spaces; grouping algorithm; irregular clusters; natural scenes; nonparametric clustering algorithm; perceptually salient image regions; pixel mapping; unbalanced clusters; Clustering algorithms; Computer vision; Content based retrieval; Gaussian processes; Image retrieval; Image segmentation; Layout; Libraries; Mathematics; Robustness;
Conference_Titel :
Computer Vision, 1999. The Proceedings of the Seventh IEEE International Conference on
Conference_Location :
Kerkyra
Print_ISBN :
0-7695-0164-8
DOI :
10.1109/ICCV.1999.790377