Skeletonization via distance maps and level sets

Ron Kimmel*, Doron Shaked, Nahum Kiryati, A. M. Bruckstein

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


The medial axis transform (MAT) of a shape, better known as its skeleton, is frequently used in shape analysis and related areas. In this paper a new approach for determining the skeleton of an object, is presented. The boundary is segmented at points of maximal positive curvature and a distance map from each of the segments is calculated. The skeleton is then located by applying simple rules to the zero sets of distance maps differences. A framework is proposed for numerical approximation of distance maps that is consistent with the continuous case, hence does not suffer from digitization bias due to metrication errors of the implementation on the grid. Subpixel accuracy in distance map calculation is obtained by using gray level information along the boundary of the shape in the numerical scheme. The accuracy of the resulting efficient skeletonization algorithm is demonstrated by several examples.

Original languageEnglish
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
EditorsRobert A. Melter, Angela Y. Wu
Number of pages12
StatePublished - 1995
Externally publishedYes
EventVision Geometry III - Boston, MA, USA
Duration: 2 Nov 19943 Nov 1994

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X


ConferenceVision Geometry III
CityBoston, MA, USA


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