Loading…

A parallel Homological Spanning Forest framework for 2D topological image analysis

•A framework for topological computation in a pre-segmented 2D digital image.•A new mathematical model for digital objects: primal–dual abstract cell complex.•It is oriented to maximize the degree of parallelization for parallel computers.•Algorithms avoid iterative and conditional sentences.•Comple...

Full description

Saved in:
Bibliographic Details
Published in:Pattern recognition letters 2016-11, Vol.83 (1), p.49-58
Main Authors: Diaz-del-Rio, Fernando, Real, Pedro, Onchis, Darian M.
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c701t-7fd2471cfe3e31154ad39fd5abe06a60b410ac508436bfd9e3886250a168e87d3
cites cdi_FETCH-LOGICAL-c701t-7fd2471cfe3e31154ad39fd5abe06a60b410ac508436bfd9e3886250a168e87d3
container_end_page 58
container_issue 1
container_start_page 49
container_title Pattern recognition letters
container_volume 83
creator Diaz-del-Rio, Fernando
Real, Pedro
Onchis, Darian M.
description •A framework for topological computation in a pre-segmented 2D digital image.•A new mathematical model for digital objects: primal–dual abstract cell complex.•It is oriented to maximize the degree of parallelization for parallel computers.•Algorithms avoid iterative and conditional sentences.•Complex data structures have been avoided to promote efficient parallelism. In [14], a topologically consistent framework to support parallel topological analysis and recognition for 2D digital objects was introduced. Based on this theoretical work, we focus on the problem of finding efficient algorithmic solutions for topological interrogation of a 2D digital object of interest D of a pre-segmented digital image I, using 4-adjacency between pixels of D. In order to maximize the degree of parallelization of the topological processes, we use as many elementary unit processing as pixels the image I has. The mathematical model underlying this framework is an appropriate extension of the classical concept of abstract cell complex: a primal–dual abstract cell complex (pACC for short). This versatile data structure encompasses the notion of Homological Spanning Forest fostered in [14,15]. Starting from a symmetric pACC associated with I, the modus operandi is to construct via combinatorial operations another asymmetric one presenting the maximal number of non-null primal elementary interactions between the cells of D. The fundamental topological tools have been transformed so as to promote an efficient parallel implementation in any parallel-oriented architecture (GPUs, multi-threaded computers, SIMD kernels and so on). A software prototype modeling such a parallel framework is built.
doi_str_mv 10.1016/j.patrec.2016.07.023
format article
fullrecord <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_6289248</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S016786551630201X</els_id><sourcerecordid>2084460478</sourcerecordid><originalsourceid>FETCH-LOGICAL-c701t-7fd2471cfe3e31154ad39fd5abe06a60b410ac508436bfd9e3886250a168e87d3</originalsourceid><addsrcrecordid>eNp9kUtv1DAUhS1ERaeFf4BQJDZsEq4fsT0bpKq0FKlSJR5ry-PcDB6cONiZVv339TBleCxYWdY9_nzOPYS8pNBQoPLtppnsnNA1rNwaUA0w_oQsqFasVlyIp2RRBqrWsm2PyUnOGwCQfKmfkWMOrZBU0wX5dFZNNtkQMFRXcYghrr2zofo82XH047q6jAnzXPXJDngX0_eqj6li76s5TgexH-waKzvacJ99fk6Oehsyvng8T8nXy4sv51f19c2Hj-dn17VTQOda9R0TiroeOXJKW2E7vuy71q4QpJWwEhSsa0ELLld9t0SutWQtWCo1atXxU_Juz522qwE7h-NcgpgpFTvp3kTrzd-T0X8z63hrJNNLJnQBvHkEpPhjW1KawWeHIdgR4zYbRlslJZOMF-nrf6SbuE0lcFEVh0KCUDug2Ktcijkn7A9mKJhdaWZj9qWZXWkGlIGf8Fd_Bjk8-tXS76RY1nnrMZnsPI4OO19Ys-mi__8PDyEkqr8</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2084460478</pqid></control><display><type>article</type><title>A parallel Homological Spanning Forest framework for 2D topological image analysis</title><source>Elsevier:Jisc Collections:Elsevier Read and Publish Agreement 2022-2024:Freedom Collection (Reading list)</source><creator>Diaz-del-Rio, Fernando ; Real, Pedro ; Onchis, Darian M.</creator><creatorcontrib>Diaz-del-Rio, Fernando ; Real, Pedro ; Onchis, Darian M.</creatorcontrib><description>•A framework for topological computation in a pre-segmented 2D digital image.•A new mathematical model for digital objects: primal–dual abstract cell complex.•It is oriented to maximize the degree of parallelization for parallel computers.•Algorithms avoid iterative and conditional sentences.•Complex data structures have been avoided to promote efficient parallelism. In [14], a topologically consistent framework to support parallel topological analysis and recognition for 2D digital objects was introduced. Based on this theoretical work, we focus on the problem of finding efficient algorithmic solutions for topological interrogation of a 2D digital object of interest D of a pre-segmented digital image I, using 4-adjacency between pixels of D. In order to maximize the degree of parallelization of the topological processes, we use as many elementary unit processing as pixels the image I has. The mathematical model underlying this framework is an appropriate extension of the classical concept of abstract cell complex: a primal–dual abstract cell complex (pACC for short). This versatile data structure encompasses the notion of Homological Spanning Forest fostered in [14,15]. Starting from a symmetric pACC associated with I, the modus operandi is to construct via combinatorial operations another asymmetric one presenting the maximal number of non-null primal elementary interactions between the cells of D. The fundamental topological tools have been transformed so as to promote an efficient parallel implementation in any parallel-oriented architecture (GPUs, multi-threaded computers, SIMD kernels and so on). A software prototype modeling such a parallel framework is built.</description><identifier>ISSN: 0167-8655</identifier><identifier>EISSN: 1872-7344</identifier><identifier>DOI: 10.1016/j.patrec.2016.07.023</identifier><identifier>PMID: 30546181</identifier><language>eng</language><publisher>Netherlands: Elsevier B.V</publisher><subject>2D digital image ; Algorithms ; Combinatorial analysis ; Computational algebraic topology ; Computer simulation ; Computers ; Data structures ; Digital imaging ; Forests ; Homological Spanning Forest ; Homology ; Image analysis ; Image processing ; Interrogation ; Mathematical models ; Object recognition ; Parallel algorithm ; Parallel processing ; Pixels ; Primal–dual abstract cell complex ; Prototypes ; Software ; Symmetry ; Topological analysis ; Topology ; Two dimensional analysis</subject><ispartof>Pattern recognition letters, 2016-11, Vol.83 (1), p.49-58</ispartof><rights>2016 Elsevier B.V.</rights><rights>Copyright Elsevier Science Ltd. Nov 1, 2016</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c701t-7fd2471cfe3e31154ad39fd5abe06a60b410ac508436bfd9e3886250a168e87d3</citedby><cites>FETCH-LOGICAL-c701t-7fd2471cfe3e31154ad39fd5abe06a60b410ac508436bfd9e3886250a168e87d3</cites><orcidid>0000-0001-6184-1629</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30546181$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Diaz-del-Rio, Fernando</creatorcontrib><creatorcontrib>Real, Pedro</creatorcontrib><creatorcontrib>Onchis, Darian M.</creatorcontrib><title>A parallel Homological Spanning Forest framework for 2D topological image analysis</title><title>Pattern recognition letters</title><addtitle>Pattern Recognit Lett</addtitle><description>•A framework for topological computation in a pre-segmented 2D digital image.•A new mathematical model for digital objects: primal–dual abstract cell complex.•It is oriented to maximize the degree of parallelization for parallel computers.•Algorithms avoid iterative and conditional sentences.•Complex data structures have been avoided to promote efficient parallelism. In [14], a topologically consistent framework to support parallel topological analysis and recognition for 2D digital objects was introduced. Based on this theoretical work, we focus on the problem of finding efficient algorithmic solutions for topological interrogation of a 2D digital object of interest D of a pre-segmented digital image I, using 4-adjacency between pixels of D. In order to maximize the degree of parallelization of the topological processes, we use as many elementary unit processing as pixels the image I has. The mathematical model underlying this framework is an appropriate extension of the classical concept of abstract cell complex: a primal–dual abstract cell complex (pACC for short). This versatile data structure encompasses the notion of Homological Spanning Forest fostered in [14,15]. Starting from a symmetric pACC associated with I, the modus operandi is to construct via combinatorial operations another asymmetric one presenting the maximal number of non-null primal elementary interactions between the cells of D. The fundamental topological tools have been transformed so as to promote an efficient parallel implementation in any parallel-oriented architecture (GPUs, multi-threaded computers, SIMD kernels and so on). A software prototype modeling such a parallel framework is built.</description><subject>2D digital image</subject><subject>Algorithms</subject><subject>Combinatorial analysis</subject><subject>Computational algebraic topology</subject><subject>Computer simulation</subject><subject>Computers</subject><subject>Data structures</subject><subject>Digital imaging</subject><subject>Forests</subject><subject>Homological Spanning Forest</subject><subject>Homology</subject><subject>Image analysis</subject><subject>Image processing</subject><subject>Interrogation</subject><subject>Mathematical models</subject><subject>Object recognition</subject><subject>Parallel algorithm</subject><subject>Parallel processing</subject><subject>Pixels</subject><subject>Primal–dual abstract cell complex</subject><subject>Prototypes</subject><subject>Software</subject><subject>Symmetry</subject><subject>Topological analysis</subject><subject>Topology</subject><subject>Two dimensional analysis</subject><issn>0167-8655</issn><issn>1872-7344</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><recordid>eNp9kUtv1DAUhS1ERaeFf4BQJDZsEq4fsT0bpKq0FKlSJR5ry-PcDB6cONiZVv339TBleCxYWdY9_nzOPYS8pNBQoPLtppnsnNA1rNwaUA0w_oQsqFasVlyIp2RRBqrWsm2PyUnOGwCQfKmfkWMOrZBU0wX5dFZNNtkQMFRXcYghrr2zofo82XH047q6jAnzXPXJDngX0_eqj6li76s5TgexH-waKzvacJ99fk6Oehsyvng8T8nXy4sv51f19c2Hj-dn17VTQOda9R0TiroeOXJKW2E7vuy71q4QpJWwEhSsa0ELLld9t0SutWQtWCo1atXxU_Juz522qwE7h-NcgpgpFTvp3kTrzd-T0X8z63hrJNNLJnQBvHkEpPhjW1KawWeHIdgR4zYbRlslJZOMF-nrf6SbuE0lcFEVh0KCUDug2Ktcijkn7A9mKJhdaWZj9qWZXWkGlIGf8Fd_Bjk8-tXS76RY1nnrMZnsPI4OO19Ys-mi__8PDyEkqr8</recordid><startdate>20161101</startdate><enddate>20161101</enddate><creator>Diaz-del-Rio, Fernando</creator><creator>Real, Pedro</creator><creator>Onchis, Darian M.</creator><general>Elsevier B.V</general><general>Elsevier Science Ltd</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7TK</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0001-6184-1629</orcidid></search><sort><creationdate>20161101</creationdate><title>A parallel Homological Spanning Forest framework for 2D topological image analysis</title><author>Diaz-del-Rio, Fernando ; Real, Pedro ; Onchis, Darian M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c701t-7fd2471cfe3e31154ad39fd5abe06a60b410ac508436bfd9e3886250a168e87d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>2D digital image</topic><topic>Algorithms</topic><topic>Combinatorial analysis</topic><topic>Computational algebraic topology</topic><topic>Computer simulation</topic><topic>Computers</topic><topic>Data structures</topic><topic>Digital imaging</topic><topic>Forests</topic><topic>Homological Spanning Forest</topic><topic>Homology</topic><topic>Image analysis</topic><topic>Image processing</topic><topic>Interrogation</topic><topic>Mathematical models</topic><topic>Object recognition</topic><topic>Parallel algorithm</topic><topic>Parallel processing</topic><topic>Pixels</topic><topic>Primal–dual abstract cell complex</topic><topic>Prototypes</topic><topic>Software</topic><topic>Symmetry</topic><topic>Topological analysis</topic><topic>Topology</topic><topic>Two dimensional analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Diaz-del-Rio, Fernando</creatorcontrib><creatorcontrib>Real, Pedro</creatorcontrib><creatorcontrib>Onchis, Darian M.</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Pattern recognition letters</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Diaz-del-Rio, Fernando</au><au>Real, Pedro</au><au>Onchis, Darian M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A parallel Homological Spanning Forest framework for 2D topological image analysis</atitle><jtitle>Pattern recognition letters</jtitle><addtitle>Pattern Recognit Lett</addtitle><date>2016-11-01</date><risdate>2016</risdate><volume>83</volume><issue>1</issue><spage>49</spage><epage>58</epage><pages>49-58</pages><issn>0167-8655</issn><eissn>1872-7344</eissn><abstract>•A framework for topological computation in a pre-segmented 2D digital image.•A new mathematical model for digital objects: primal–dual abstract cell complex.•It is oriented to maximize the degree of parallelization for parallel computers.•Algorithms avoid iterative and conditional sentences.•Complex data structures have been avoided to promote efficient parallelism. In [14], a topologically consistent framework to support parallel topological analysis and recognition for 2D digital objects was introduced. Based on this theoretical work, we focus on the problem of finding efficient algorithmic solutions for topological interrogation of a 2D digital object of interest D of a pre-segmented digital image I, using 4-adjacency between pixels of D. In order to maximize the degree of parallelization of the topological processes, we use as many elementary unit processing as pixels the image I has. The mathematical model underlying this framework is an appropriate extension of the classical concept of abstract cell complex: a primal–dual abstract cell complex (pACC for short). This versatile data structure encompasses the notion of Homological Spanning Forest fostered in [14,15]. Starting from a symmetric pACC associated with I, the modus operandi is to construct via combinatorial operations another asymmetric one presenting the maximal number of non-null primal elementary interactions between the cells of D. The fundamental topological tools have been transformed so as to promote an efficient parallel implementation in any parallel-oriented architecture (GPUs, multi-threaded computers, SIMD kernels and so on). A software prototype modeling such a parallel framework is built.</abstract><cop>Netherlands</cop><pub>Elsevier B.V</pub><pmid>30546181</pmid><doi>10.1016/j.patrec.2016.07.023</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0001-6184-1629</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 0167-8655
ispartof Pattern recognition letters, 2016-11, Vol.83 (1), p.49-58
issn 0167-8655
1872-7344
language eng
recordid cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_6289248
source Elsevier:Jisc Collections:Elsevier Read and Publish Agreement 2022-2024:Freedom Collection (Reading list)
subjects 2D digital image
Algorithms
Combinatorial analysis
Computational algebraic topology
Computer simulation
Computers
Data structures
Digital imaging
Forests
Homological Spanning Forest
Homology
Image analysis
Image processing
Interrogation
Mathematical models
Object recognition
Parallel algorithm
Parallel processing
Pixels
Primal–dual abstract cell complex
Prototypes
Software
Symmetry
Topological analysis
Topology
Two dimensional analysis
title A parallel Homological Spanning Forest framework for 2D topological image analysis
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-27T22%3A36%3A44IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20parallel%20Homological%20Spanning%20Forest%20framework%20for%202D%20topological%20image%20analysis&rft.jtitle=Pattern%20recognition%20letters&rft.au=Diaz-del-Rio,%20Fernando&rft.date=2016-11-01&rft.volume=83&rft.issue=1&rft.spage=49&rft.epage=58&rft.pages=49-58&rft.issn=0167-8655&rft.eissn=1872-7344&rft_id=info:doi/10.1016/j.patrec.2016.07.023&rft_dat=%3Cproquest_pubme%3E2084460478%3C/proquest_pubme%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c701t-7fd2471cfe3e31154ad39fd5abe06a60b410ac508436bfd9e3886250a168e87d3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2084460478&rft_id=info:pmid/30546181&rfr_iscdi=true