DTW for Matching Radon Features: A Pattern Recognition and Retrieval Method
Identifieur interne : 001A46 ( Hal/Curation ); précédent : 001A45; suivant : 001A47DTW for Matching Radon Features: A Pattern Recognition and Retrieval Method
Auteurs : Santosh K. C. [France] ; Bart Lamiroy [France] ; Laurent Wendling [France]Source :
English descriptors
Abstract
In this paper, we present a method for pattern such as graphical symbol and shape recognition and retrieval. It is basically based on dynamic programming for matching the Radon features. The key characteristic of the method is to use DTW algorithm to match corresponding pairs of histograms at every projecting angle. This allows to exploit the Radon property to include both boundary as internal structure of shapes, while avoiding compressing pattern representation into a single vector and thus miss information, thanks to the DTW. Experimental results show that the method is robust to distortion and degradation including affine transformations.
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DOI: 10.1007/978-3-642-23687-7_23
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Paris 5</orgName><orgName type="acronym">UPD5</orgName><desc><address><addrLine>12, rue de l'École de Médecine - 75270 Paris cedex 06</addrLine><country key="FR"></country></address><ref type="url">http://www.parisdescartes.fr/</ref></desc></org></tutelle></tutelles></hal:affiliation><country>France</country></affiliation></author></analytic><idno type="DOI">10.1007/978-3-642-23687-7_23</idno></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="mix" xml:lang="en"><term>DTW</term><term>Pattern Recognition and Retrieval</term><term>Radon Transform</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">In this paper, we present a method for pattern such as graphical symbol and shape recognition and retrieval. It is basically based on dynamic programming for matching the Radon features. The key characteristic of the method is to use DTW algorithm to match corresponding pairs of histograms at every projecting angle. This allows to exploit the Radon property to include both boundary as internal structure of shapes, while avoiding compressing pattern representation into a single vector and thus miss information, thanks to the DTW. Experimental results show that the method is robust to distortion and degradation including affine transformations.</div></front></TEI><hal api="V3"><titleStmt><title xml:lang="en">DTW for Matching Radon Features: A Pattern Recognition and Retrieval Method</title><author role="aut"><persName><forename type="first">Santosh</forename><surname>K.C.</surname></persName><email>Santosh.KC@inria.fr</email><idno type="halauthor">636695</idno><affiliation ref="#struct-119680"></affiliation></author><author role="aut"><persName><forename type="first">Bart</forename><surname>Lamiroy</surname></persName><email>Bart.Lamiroy@loria.fr</email><idno type="idhal">bart-lamiroy</idno><idno type="halauthor">131730</idno><idno type="ResearcherId">http://www.researcherid.com/rid/A-7746-2010</idno><idno type="IdRef">http://www.idref.fr/111726980</idno><idno type="ORCID">http://orcid.org/0000-0003-0871-0149</idno><orgName ref="#struct-364480"></orgName><affiliation ref="#struct-119680"></affiliation></author><author role="aut"><persName><forename type="first">Laurent</forename><surname>Wendling</surname></persName><email>Laurent.Wendling@math-info.univ-paris5.fr</email><idno type="halauthor">525575</idno><affiliation ref="#struct-103372"></affiliation></author><editor role="depositor"><persName><forename>Santosh</forename><surname>K.C.</surname></persName><email>kcsantsa@loria.fr</email></editor></titleStmt><editionStmt><edition n="v1" type="current"><date type="whenSubmitted">2011-08-26 17:41:03</date><date type="whenWritten">2011-01-19</date><date type="whenModified">2016-05-19 01:04:24</date><date type="whenReleased">2011-08-29 08:14:36</date><date type="whenProduced">2011-08-22</date><date type="whenEndEmbargoed">2011-08-26</date><ref type="file" target="https://hal.inria.fr/inria-00617287/document"><date notBefore="2011-08-26"></date></ref><ref type="file" subtype="author" n="1" target="https://hal.inria.fr/inria-00617287/file/santosh_Acivs11.pdf"><date notBefore="2011-08-26"></date></ref></edition><respStmt><resp>contributor</resp><name key="136106"><persName><forename>Santosh</forename><surname>K.C.</surname></persName><email>kcsantsa@loria.fr</email></name></respStmt></editionStmt><publicationStmt><distributor>CCSD</distributor><idno type="halId">inria-00617287</idno><idno type="halUri">https://hal.inria.fr/inria-00617287</idno><idno type="halBibtex">kc:inria-00617287</idno><idno type="halRefHtml">Jacques Blanc-Talon and Richard P. Kleihorst and Wilfried Philips and Dan C. Popescu and Paul Scheunders. Advanced Concepts for Intelligent Vision Systems, Aug 2011, Ghent, Belgium. Springer, 6915, pp.249--260, 2011, 13th International Conference on Advanced Concepts for Intelligent Vision Systems - ACIVS 2011. <http://dx.doi.org/10.1007/978-3-642-23687-7_23>. <10.1007/978-3-642-23687-7_23></idno><idno type="halRef">Jacques Blanc-Talon and Richard P. Kleihorst and Wilfried Philips and Dan C. Popescu and Paul Scheunders. Advanced Concepts for Intelligent Vision Systems, Aug 2011, Ghent, Belgium. Springer, 6915, pp.249--260, 2011, 13th International Conference on Advanced Concepts for Intelligent Vision Systems - ACIVS 2011. <http://dx.doi.org/10.1007/978-3-642-23687-7_23>. <10.1007/978-3-642-23687-7_23></idno></publicationStmt><seriesStmt><idno type="stamp" n="UNIV-PARIS5">Université Paris Descartes (Paris 5)</idno><idno type="stamp" n="CNRS">CNRS - Centre national de la recherche scientifique</idno><idno type="stamp" n="INRIA">INRIA - Institut National de Recherche en Informatique et en Automatique</idno><idno type="stamp" n="INPL">Institut National Polytechnique de Lorraine</idno><idno type="stamp" n="LABO-LORIA-SET" p="LORIA">LABO-LORIA-SET</idno><idno type="stamp" n="LORIA2">Publications du LORIA</idno><idno type="stamp" n="LIPADE">Laboratoire d'Informatique PAris DEscartes - EA 2517</idno><idno type="stamp" n="LORIA">LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications</idno><idno type="stamp" n="LORIA-TALC" p="LORIA">Traitement automatique des langues et des connaissances</idno><idno type="stamp" n="UNIV-LORRAINE">Université de Lorraine</idno></seriesStmt><notesStmt><note type="commentary">The original publication is available at www.springerlink.com</note><note type="audience" n="2">International</note><note type="invited" n="0">No</note><note type="popular" n="0">No</note><note type="peer" n="1">Yes</note><note type="proceedings" n="1">Yes</note></notesStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">DTW for Matching Radon Features: A Pattern Recognition and Retrieval Method</title><author role="aut"><persName><forename type="first">Santosh</forename><surname>K.C.</surname></persName><email>Santosh.KC@inria.fr</email><idno type="halAuthorId">636695</idno><affiliation ref="#struct-119680"></affiliation></author><author role="aut"><persName><forename type="first">Bart</forename><surname>Lamiroy</surname></persName><email>Bart.Lamiroy@loria.fr</email><idno type="idHal">bart-lamiroy</idno><idno type="halAuthorId">131730</idno><idno type="ResearcherId">http://www.researcherid.com/rid/A-7746-2010</idno><idno type="IdRef">http://www.idref.fr/111726980</idno><idno type="ORCID">http://orcid.org/0000-0003-0871-0149</idno><orgName ref="#struct-364480"></orgName><affiliation ref="#struct-119680"></affiliation></author><author role="aut"><persName><forename type="first">Laurent</forename><surname>Wendling</surname></persName><email>Laurent.Wendling@math-info.univ-paris5.fr</email><idno type="halAuthorId">525575</idno><affiliation ref="#struct-103372"></affiliation></author></analytic><monogr><meeting><title>Advanced Concepts for Intelligent Vision Systems</title><date type="start">2011-08-22</date><date type="end">2011-08-25</date><settlement>Ghent</settlement><country key="BE">Belgium</country></meeting><editor>Jacques Blanc-Talon and Richard P. Kleihorst and Wilfried Philips and Dan C. Popescu and Paul Scheunders</editor><imprint><publisher>Springer</publisher><biblScope unit="serie">13th International Conference on Advanced Concepts for Intelligent Vision Systems - ACIVS 2011</biblScope><biblScope unit="volume">6915</biblScope><biblScope unit="pp">249--260</biblScope><date type="datePub">2011-08-22</date></imprint></monogr><idno type="doi">10.1007/978-3-642-23687-7_23</idno><ref type="publisher">http://dx.doi.org/10.1007/978-3-642-23687-7_23</ref></biblStruct></sourceDesc><profileDesc><langUsage><language ident="en">English</language></langUsage><textClass><keywords scheme="author"><term xml:lang="en">Radon Transform</term><term xml:lang="en">DTW</term><term xml:lang="en">Pattern Recognition and Retrieval</term></keywords><classCode scheme="halDomain" n="info.info-cv">Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]</classCode><classCode scheme="halTypology" n="COMM">Conference papers</classCode></textClass><abstract xml:lang="en">In this paper, we present a method for pattern such as graphical symbol and shape recognition and retrieval. It is basically based on dynamic programming for matching the Radon features. The key characteristic of the method is to use DTW algorithm to match corresponding pairs of histograms at every projecting angle. This allows to exploit the Radon property to include both boundary as internal structure of shapes, while avoiding compressing pattern representation into a single vector and thus miss information, thanks to the DTW. Experimental results show that the method is robust to distortion and degradation including affine transformations.</abstract></profileDesc></hal></record>Pour manipuler ce document sous Unix (Dilib)
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