1-Attempt parallel thinning
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...
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Veröffentlicht in: | Journal of combinatorial optimization 2022-11, Vol.44 (4), p.2395-2409 |
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creator | Palágyi, Kálmán Németh, Gábor |
description | 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
≥
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. |
doi_str_mv | 10.1007/s10878-021-00744-y |
format | Article |
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k
-attempt thinning (
k
≥
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.</description><identifier>ISSN: 1382-6905</identifier><identifier>EISSN: 1573-2886</identifier><identifier>DOI: 10.1007/s10878-021-00744-y</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Algorithms ; Combinatorial analysis ; Combinatorics ; Convex and Discrete Geometry ; Image analysis ; Iterative methods ; Mathematical Modeling and Industrial Mathematics ; Mathematics ; Mathematics and Statistics ; Operations Research/Decision Theory ; Optimization ; Theory of Computation ; Thinning ; Topology</subject><ispartof>Journal of combinatorial optimization, 2022-11, Vol.44 (4), p.2395-2409</ispartof><rights>The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021</rights><rights>The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c200t-5e91271cf0b453d6364dcc77afe6f3ce139c45bdc309a7bfba44c39f94d2e4773</cites><orcidid>0000-0002-3274-7315</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10878-021-00744-y$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10878-021-00744-y$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids></links><search><creatorcontrib>Palágyi, Kálmán</creatorcontrib><creatorcontrib>Németh, Gábor</creatorcontrib><title>1-Attempt parallel thinning</title><title>Journal of combinatorial optimization</title><addtitle>J Comb Optim</addtitle><description>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
≥
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.</description><subject>Algorithms</subject><subject>Combinatorial analysis</subject><subject>Combinatorics</subject><subject>Convex and Discrete Geometry</subject><subject>Image analysis</subject><subject>Iterative methods</subject><subject>Mathematical Modeling and Industrial Mathematics</subject><subject>Mathematics</subject><subject>Mathematics and Statistics</subject><subject>Operations Research/Decision Theory</subject><subject>Optimization</subject><subject>Theory of Computation</subject><subject>Thinning</subject><subject>Topology</subject><issn>1382-6905</issn><issn>1573-2886</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNp9kEtPwzAQhC0EEqXwB-BSibNh_Y6PVcVLqsQFzpbj2CVVmgTbPeTfYwgSN047K83Mrj6ErgncEQB1nwhUqsJACS4r53g6QQsiFMO0quRp0ayiWGoQ5-gipT0AFM0X6Ibgdc7-MObVaKPtOt-t8kfb922_u0RnwXbJX_3OJXp_fHjbPOPt69PLZr3FjgJkLLwmVBEXoOaCNZJJ3jinlA1eBuY8YdpxUTeOgbaqDrXl3DEdNG-o50qxJbqde8c4fB59ymY_HGNfThqqKC-PSi2Ki84uF4eUog9mjO3BxskQMN8QzAzBFAjmB4KZSojNoVTM_c7Hv-p_Ul-iR15V</recordid><startdate>20221101</startdate><enddate>20221101</enddate><creator>Palágyi, Kálmán</creator><creator>Németh, Gábor</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><orcidid>https://orcid.org/0000-0002-3274-7315</orcidid></search><sort><creationdate>20221101</creationdate><title>1-Attempt parallel thinning</title><author>Palágyi, Kálmán ; Németh, Gábor</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c200t-5e91271cf0b453d6364dcc77afe6f3ce139c45bdc309a7bfba44c39f94d2e4773</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Algorithms</topic><topic>Combinatorial analysis</topic><topic>Combinatorics</topic><topic>Convex and Discrete Geometry</topic><topic>Image analysis</topic><topic>Iterative methods</topic><topic>Mathematical Modeling and Industrial Mathematics</topic><topic>Mathematics</topic><topic>Mathematics and Statistics</topic><topic>Operations Research/Decision Theory</topic><topic>Optimization</topic><topic>Theory of Computation</topic><topic>Thinning</topic><topic>Topology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Palágyi, Kálmán</creatorcontrib><creatorcontrib>Németh, Gábor</creatorcontrib><collection>CrossRef</collection><jtitle>Journal of combinatorial optimization</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Palágyi, Kálmán</au><au>Németh, Gábor</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>1-Attempt parallel thinning</atitle><jtitle>Journal of combinatorial optimization</jtitle><stitle>J Comb Optim</stitle><date>2022-11-01</date><risdate>2022</risdate><volume>44</volume><issue>4</issue><spage>2395</spage><epage>2409</epage><pages>2395-2409</pages><issn>1382-6905</issn><eissn>1573-2886</eissn><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
≥
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.</abstract><cop>New York</cop><pub>Springer US</pub><doi>10.1007/s10878-021-00744-y</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0002-3274-7315</orcidid></addata></record> |
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subjects | Algorithms Combinatorial analysis Combinatorics Convex and Discrete Geometry Image analysis Iterative methods Mathematical Modeling and Industrial Mathematics Mathematics Mathematics and Statistics Operations Research/Decision Theory Optimization Theory of Computation Thinning Topology |
title | 1-Attempt parallel thinning |
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