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Boundary Detection in Multidimensions
January 1982 (vol. 4 no. 1)
pp. 41-50
Jayaram K. Udupa, Medical Image Processing Group, Department of Computer Science, State University of New York at Buffalo, Amherst, NY 14226; Medical Image Processing Group, Department of Radiology,
Sargur N. Srihari, MEMBER, IEEE, Department of Computer Science, State University of New York at Buffalo, Amherst, NY 14226.
Gabor T. Herman, MEMBER, IEEE, Medical Image Processing Group, Department of Computer Science, State University of New York at Buffalo, Amherst, NY 14226; Medical Image Processing Group, Department
The development of image processing algorithms for time-varying imagery and computerized tomography data calls for generalization of the concepts of adjacency, connectivity, boundary, etc., to three and four-dimensional discrete spaces. This paper defines these basic concepts in unified terminology and presents algorithms for a boundary detection task in multidimensional space. The performance of these algorithms is discussed with respect to theoretical maximum complexity, and is illustrated with simulated computerized tomography data.
Citation:
Jayaram K. Udupa, Sargur N. Srihari, Gabor T. Herman, "Boundary Detection in Multidimensions," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 4, no. 1, pp. 41-50, Jan. 1982, doi:10.1109/TPAMI.1982.4767193
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