CSDL Home IEEE Transactions on Pattern Analysis & Machine Intelligence 2008 vol.30 Issue No.12 - December

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Issue No.12 - December (2008 vol.30)

pp: 2204-2217

Wim H. Hesselink , University of Groningen, Groningen

Jos B.T.M. Roerdink , University of Groningen, Groningen

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TPAMI.2008.21

ABSTRACT

A general algorithm for computing Euclidean skeletons of 2D and 3D data sets in linear time is presented. These skeletons are defined in terms of a new concept, called the integer medial axis (IMA) transform. We prove a number of fundamental properties of the IMA skeleton, and compare these with properties of the CMD (centers of maximal disks) skeleton. Several pruning methods for IMA skeletons are introduced (constant, linear and square-root pruning) and their properties studied. The algorithm for computing the IMA skeleton is based upon the feature transform, using a modification of a linear-time algorithm for Euclidean distance transforms. The skeletonization algorithm has a time complexity which is linear in the number of input points, and can be easily parallelized. We present experimental results for several data sets, looking at skeleton quality, memory usage and computation time, both for 2D images and 3D volumes.

INDEX TERMS

Curve, surface, solid, and object representations, Image Representation, Edge and feature detection, Feature representation, Shape, Volume visualization

CITATION

Wim H. Hesselink, Jos B.T.M. Roerdink, "Euclidean Skeletons of Digital Image and Volume Data in Linear Time by the Integer Medial Axis Transform",

*IEEE Transactions on Pattern Analysis & Machine Intelligence*, vol.30, no. 12, pp. 2204-2217, December 2008, doi:10.1109/TPAMI.2008.21REFERENCES