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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Vydané v:	Pattern recognition letters Ročník 76; s. 3 - 12
Hlavní autori:	Saha, Punam K., Borgefors, Gunilla, Sanniti di Baja, Gabriella
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 01.06.2016
Predmet:	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
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Abstract	•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.
AbstractList	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. •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.
Author	Sanniti di Baja, Gabriella Borgefors, Gunilla Saha, Punam K.
Author_xml	– sequence: 1 givenname: Punam K. surname: Saha fullname: Saha, Punam K. email: punam-saha@uiowa.edu, pksaha@engineering.uiowa.edu, pksaha@healthcare.uiowa.edu organization: Department of Electrical and Computer Engineering, University of Iowa, Iowa City, IA, USA – sequence: 2 givenname: Gunilla surname: Borgefors fullname: Borgefors, Gunilla organization: Centre for Image Analysis, Uppsala University, Uppsala, Sweden – sequence: 3 givenname: Gabriella orcidid: 0000-0003-2218-0412 surname: Sanniti di Baja fullname: Sanniti di Baja, Gabriella organization: Institute of Cybernetics “E.Caianiello”, CNR, 80078 Pozzuoli, Naples, Italy
BackLink	https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-266313$$DView record from Swedish Publication Index (Uppsala universitet)
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Snippet	•A comprehensive survey of skeletonization algorithms and their applications.•Different Skeletonization approaches are summarized.•Topology preservation and... Skeletonization provides an effective and compact representation of objects, which is useful for object description, retrieval, manipulation, matching,...
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SubjectTerms	Applications Centers of maximal balls Computerized Image Processing Datoriserad bildbehandling Distance transform Parallel algorithms Skeletonization Topology preservation
Title	A survey on skeletonization algorithms and their applications
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