Abstract
This chapter takes another look at filament skeletons, skeletal vortexes and skeletal nerves in cell complexes. The focus here is on the group theory underlying a Computational Topology of digital images (CTdi). A digital image is an example of what is known as a shape space. A space is any nonempty set of points. A shape space is a collection of sets of points X and each particular configuration (arrangement of the points) in a subset of X defines a shape. A digital image shape space is a collection of digitized optical sensor values that provide a record of the hue angles of pixels in the Hue Saturation Value colour space. There is a 1-to-1 correspondence between the pixel hue angles and the wavelengths of light reflected from the surfaces in a visual scene at a given instant in spacetime. It is this 1-to-1 correspondence that leads to a deeper view of skeletal complexes on triangulated video frames.
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Notes
- 1.
Many thanks to S. Ramanna for providing these Apple iPad \(^{{\textregistered }}\) images.
- 2.
Many thanks to M. Z. Ahmad for supplying the Matlab script used to draw a barycentric filament skeleton.
- 3.
Many thanks to R. Tozzi and A. Tozzi for the Napoli breakfast picture.
- 4.
Many thanks to Alexander Yurkin for supplying this self-portrait of his father.
- 5.
Many thanks to Arjuna P. H. Don for this sample triangulated video frame.
- 6.
Many thanks to Fatemeh Gorgannejad for correcting this example.
- 7.
Many thanks to Enze Cui for the video frame in this example.
- 8.
This is also a video frame from Enze Cui.
- 9.
See F. Haimo’s review MR0067879 at https://mathscinet.ams.org/mathscinet/.
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Peters, J.F. (2020). Shape Fingerprints, Geodesic Trails and Free Abelian Groups on Skeletal Vortexes. In: Computational Geometry, Topology and Physics of Digital Images with Applications. Intelligent Systems Reference Library, vol 162. Springer, Cham. https://doi.org/10.1007/978-3-030-22192-8_3
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