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Title: Binary and grey-value skeletons: Metrics and algorithms
Authors:
B.J.H. Verwer, L.J. van
Vliet, and P.W. Verbeek
in: C.Y. Suen, P.S.P. Wang (eds.), Thinning Methodologies for Pattern
Recognition, Machine Perception and Artificial Intelligence, vol. 8, World
Scientific, Singapore, 1994, 323- 344.
Abstract
A metric defines the distance between any two points. The 'natural'
metrics of the digital world do not approximate the Euclidean metric of
the continuous world well. Skeletonization (sometimes named topology preserving
shrinking or homotopic thinning) is one example in which this leads to
unacceptable results. In the present work we propose and demonstrate skeletonization
using path-based metrics which are a better approximation of the Euclidean
metric. Moreover, we achieve a good performance in speed by processing
each pixel only once in the calculations of binary (Hilditch) and grey-value
(upper) skeletons.
Key words
Skeletonization, thinning, topology preserving shrinking, watershed,
upper skeleton, metric, chamfer, distance transform
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