Isoperimetric Graph Partitioning for Data Clustering and Image Segmentation

Spectral methods of graph partitioning have be(oll shown to provi(k a powerful approach to the image segmentation problem. In this paper, we adopt a different approach, based on mtimating the isoperimetric constant of an image graph. Our algorithm produces the high quality segmentations and data clustering of speetral methods, but with improved speed and stability.

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