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Isoperimetric graph partitioning for image segmentation
2006
IEEE Transactions on Pattern Analysis and Machine Intelligence
Spectral graph partitioning provides a powerful approach to image segmentation. We introduce an alternate idea that finds partitions with a small isoperimetric constant, requiring solution to a linear system rather than an eigenvector problem. This approach produces the high quality segmentations of spectral methods, but with improved speed and stability.
doi:10.1109/tpami.2006.57
pmid:16526432
fatcat:rznnl4te4rfohetpdm5japusby