A skeletonization algorithm by maxima tracking on Euclidean distance transform

Abstract A simple and efficient algorithm using the maxima tracking approach on Euclidean distance transform to detect skeleton points is presented. The advantages of the skeleton obtained are: (1) connectivity preservation; (2) single-pixel in width; and (3) its locations as close as to the most symmetrical axes. Besides, the condition of the least slope change of skeleton is used to ensure the fairness of the digital medial axes. With the least effort, the algorithm can be modified to eliminate non-significant short skeletal branches originating from the object contour while the critical shape-informative medial axes are preserved.

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