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Erschienen in: Journal of Combinatorial Optimization 4/2022

24.04.2021

1-Attempt parallel thinning

verfasst von: Kálmán Palágyi, Gábor Németh

Erschienen in: Journal of Combinatorial Optimization | Ausgabe 4/2022

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Abstract

Thinning is a frequently used technique capable of producing all kinds of skeleton-like shape features in a topology-preserving way. It is an iterative object reduction: some border points of binary objects that satisfy some topological and geometrical constraints are deleted, and the entire process is repeated until stability is reached. In the conventional implementation of thinning algorithms, the deletability of all border points in the actual picture is to be investigated. That is why, we introduced the concept of k-attempt thinning (\(k\ge 1\)) in our previous work (presented in the 20th International Workshop on Combinatorial Image Analysis, IWCIA 2020). In the case of a k-attempt algorithm, if a border point ‘survives’ at least k successive iterations, it is ‘immortal’ (i.e., it cannot be deleted later). In this paper, we give a computationally efficient implementation scheme for 1-attempt thinning, and a 1-attempt 2D parallel thinning algorithm is reported. The advantage of the new implementation scheme over the conventional one is also illustrated.

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Metadaten
Titel
1-Attempt parallel thinning
verfasst von
Kálmán Palágyi
Gábor Németh
Publikationsdatum
24.04.2021
Verlag
Springer US
Erschienen in
Journal of Combinatorial Optimization / Ausgabe 4/2022
Print ISSN: 1382-6905
Elektronische ISSN: 1573-2886
DOI
https://doi.org/10.1007/s10878-021-00744-y

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