TY - GEN

T1 - Higher-dimensional segmentation by minimum-cut algorithm

AU - Ishikawa, Hiroshi

AU - Geiger, Davi

PY - 2005

Y1 - 2005

N2 - It is important in many applications of 3D and higher dimensional segmentation that the resulting segments of voxels are not required to have only one connected component, as in some of extant methods. Indeed, it is generally necessary to be able to automatically determine the appropriate number of connected components. More generally, for a larger class of applications, the segments should have no topological restrictions at all. For instance, each connected component should be allowed to have as many holes as appropriate to fit the data. We propose a method based on a graph algorithm to automatically segment 3D and higher-dimensional images into two segments without user intervention, with no topological restriction on the solution, and in such a way that the solution is optimal under a precisely defined optimization criterion.

AB - It is important in many applications of 3D and higher dimensional segmentation that the resulting segments of voxels are not required to have only one connected component, as in some of extant methods. Indeed, it is generally necessary to be able to automatically determine the appropriate number of connected components. More generally, for a larger class of applications, the segments should have no topological restrictions at all. For instance, each connected component should be allowed to have as many holes as appropriate to fit the data. We propose a method based on a graph algorithm to automatically segment 3D and higher-dimensional images into two segments without user intervention, with no topological restriction on the solution, and in such a way that the solution is optimal under a precisely defined optimization criterion.

UR - http://www.scopus.com/inward/record.url?scp=84872544674&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84872544674&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:84872544674

SN - 4901122045

SN - 9784901122047

T3 - Proceedings of the 9th IAPR Conference on Machine Vision Applications, MVA 2005

SP - 488

EP - 491

BT - Proceedings of the 9th IAPR Conference on Machine Vision Applications, MVA 2005

T2 - 9th IAPR Conference on Machine Vision Applications, MVA 2005

Y2 - 16 May 2005 through 18 May 2005

ER -