In shape analysis, skeleton (or topological skeleton) of a shape is a thin version of that shape that is equidistant to its boundaries. The skeleton usually emphasizes geometrical and topological properties of the shape, such as its connectivity, topology, length, direction, and width. Together with the distance of its points to the shape boundary, the skeleton can also serve as a representation of the shape (they contain all the information necessary to reconstruct the shape).
Skeletons have several different mathematical definitions in the technical literature, and there are many different algorithms for computing them. Various different variants of skeleton can also be found, including straight skeletons, morphological skeletons, etc.
In the technical literature, the concepts of skeleton and medial axis are used interchangeably by some authors,[1][2] while some other authors[3][4][5] regard them as related, but not the same. Similarly, the concepts of skeletonization and thinning are also regarded as identical by some,[2] and not by others.[3]
Skeletons are widely used in computer vision, image analysis, pattern recognition and digital image processing for purposes such as optical character recognition, fingerprint recognition, visual inspection or compression. Within the life sciences skeletons found extensive use to characterize protein folding[6] and plant morphology on various biological scales.[7]
- ^ Jain, Kasturi & Schunck (1995), Section 2.5.10, p. 55; Golland & Grimson (2000); Dougherty (1992); Ogniewicz (1995).
- ^ a b Gonzales & Woods (2001), Section 11.1.5, p. 650
- ^ a b A. K. Jain (1989), Section 9.9, p. 382.
- ^ Serra (1982).
- ^ Sethian (1999), Section 17.5.2, p. 234.
- ^ Abeysinghe et al. (2008)
- ^ Bucksch (2014)