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: In (Lantuéjoul 1977),[1] Lantuéjoul derived the following morphological formula for the skeleton of a continuous binary image
are the morphological erosion and opening, respectively,
, be a family of shapes, where B is a structuring element, The variable n is called the size of the structuring element.
, where: The original shape X can be reconstructed from the set of skeleton subsets
as follows: Partial reconstructions can also be performed, leading to opened versions of the original shape: Let
centered at z is called a maximal disk in a set A when: Each skeleton subset
consists of the centers of all maximal disks of size n. Morphological Skeletonization can be considered as a controlled erosion process.
This involves shrinking the image until the area of interest is 1 pixel wide.
This can allow quick and accurate image processing on an otherwise large and memory intensive operation.
A great example of using skeletonization on an image is processing fingerprints.
This can be quickly accomplished using bwmorph; a built-in Matlab function which will implement the Skeletonization Morphology technique to the image.
The image to the right shows the extent of what skeleton morphology can accomplish.
Given a partial image, it is possible to extract a much fuller picture.
Properly pre-processing the image with a simple Auto Threshold grayscale to binary converter will give the skeletonization function an easier time thinning.
The higher contrast ratio will allow the lines to joined in a more accurate manner.
Allowing to properly reconstruct the fingerprint.
