A survey on skeletonization algorithms and their applications

•A comprehensive survey of skeletonization algorithms and their applications.•Different Skeletonization approaches are summarized.•Topology preservation and parallel skeletonization are discussed.•A review of multi-scale skeletonization is presented.•Applications and performance evaluation of skelet...

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Veröffentlicht in:Pattern recognition letters Jg. 76; S. 3 - 12
Hauptverfasser: Saha, Punam K., Borgefors, Gunilla, Sanniti di Baja, Gabriella
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier B.V 01.06.2016
Schlagworte:
Applications
Centers of maximal balls
Computerized Image Processing
Datoriserad bildbehandling
Distance transform
Parallel algorithms
Skeletonization
Topology preservation
Centers of maximal balls
Skeletonization
Applications
Parallel algorithms
Topology preservation
Distance transform
ISSN:0167-8655, 1872-7344, 1872-7344
Online-Zugang:Volltext
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Zusammenfassung:•A comprehensive survey of skeletonization algorithms and their applications.•Different Skeletonization approaches are summarized.•Topology preservation and parallel skeletonization are discussed.•A review of multi-scale skeletonization is presented.•Applications and performance evaluation of skeletonization are discussed. Skeletonization provides an effective and compact representation of objects, which is useful for object description, retrieval, manipulation, matching, registration, tracking, recognition, and compression. It also facilitates efficient assessment of local object properties, e.g., scale, orientation, topology, etc. Several computational approaches are available in literature toward extracting the skeleton of an object, some of which are widely different in terms of their principles. In this paper, we present a comprehensive and concise survey of different skeletonization algorithms and discuss their principles, challenges, and benefits. Topology preservation, parallelization, and multi-scale skeletonization approaches are discussed. Finally, various applications of skeletonization are reviewed and the fundamental challenges of assessing the performance of different skeletonization algorithms are discussed.
ISSN:0167-8655
1872-7344
1872-7344
DOI:10.1016/j.patrec.2015.04.006