Morphological skeleton

In digital image processing, morphological skeleton is a skeleton (or medial axis) representation of a shape or binary image, computed by means of morphological operators.

Morphological skeletons are of two kinds:

• Those defined and by means of morphological openings, from which the original shape can be reconstructed,
• Those computed by means of the hit-or-miss transform, which preserve the shape's topology.

Skeleton by openings

Lantuéjoul's formula

Continuous images

In (Lantuéjoul 1977)^[1], Lantuéjoul derived the following morphological formula for the skeleton of a continuous binary image $X\subset \mathbb{R}^2$:

$S(X)=\bigcup_{\rho >0}\bigcap_{\mu >0}\left[(X\ominus \rho B)\setminus(X\ominus \rho B)\circ \mu B\right]$,

where $\ominus$ and $\circ$ are the morphological erosion and opening, respectively, and ρB is an open ball of radius ρ.

Discrete images

Let {nB}, $n=0,1,\ldots$, be a family of shapes, where B is a structuring element,

$nB=\underbrace{B\oplus\ldots\oplus B}_{n\mbox{ times}}$, and

0B = {o}, where o denotes the origin.

The variable n is called the size of the structuring element.

Lantuéjoul's formula has been discretized as follows. For a discrete binary image $X\subset \mathbb{Z}^2$, the skeleton S(X) is the union of the skeleton subsets {S_n(X)}, $n=0,1,\ldots,N$, where:

$S_n(X)=(X\ominus nB)\setminus(X\ominus nB)\circ B$.

Reconstruction from the skeleton

The original shape X can be reconstructed from the set of skeleton subsets {S_n(X)} as follows:

$X=\bigcup_n (S_n(X)\oplus nB)$.

Partial reconstructions can also be performed, leading to opened versions of the original shape:

$\bigcup_{n\geq m} (S_n(X)\oplus nB)=X\circ mB$.

The skeleton as the centers of the maximal disks

Let nB_z be the translated version version of nB to the point z, that is, $nB_z=\{x\in E| x-z\in nB\}$.

A shape nB_z centered at z is called a maximal disk in a set A when:

• $nB_z\in A$, and
• if, for some integer m and some point y, $nB_z\subseteq mB_y$, then $mB_y\not\subseteq A$.

Each skeleton subset S_n(X) consists of the centers of all maximal disks of size n.

Notes

1. ^ See also (Serra's 1982 book)

References

• Image Analysis and Mathematical Morphology by Jean Serra, ISBN 0126372403 (1982)
• Image Analysis and Mathematical Morphology, Volume 2: Theoretical Advances by Jean Serra, ISBN 0-12-637241-1 (1988)
• An Introduction to Morphological Image Processing by Edward R. Dougherty, ISBN 0-8194-0845-X (1992)
• Ch. Lantuéjoul, "Sur le modèle de Johnson-Mehl généralisé", Internal report of the Centre de Morph. Math., Fontainebleau, France, 1977.