Isoperimetric graph partitioning for image segmentation

L. Grady, E.L. Schwartz
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