DTW-Radon-based Shape Descriptor for Pattern Recognition
Identifieur interne : 001A47 ( Hal/Curation ); précédent : 001A46; suivant : 001A48DTW-Radon-based Shape Descriptor for Pattern Recognition
Auteurs : Santosh K. C. [France] ; Bart Lamiroy [France] ; Laurent Wendling [France]Source :
- International Journal of Pattern Recognition and Artificial Intelligence [ 0218-0014 ] ; 2013-03-27.
English descriptors
Abstract
In this paper, we present a pattern recognition method that uses dynamic programming (DP) for the alignment of Radon features. The key characteristic of the method is to use dynamic time warping (DTW) to match corresponding pairs of the Radon features for all possible projections. Thanks to DTW, we avoid compressing the feature matrix into a single vector which would otherwise miss information. To reduce the possible number of matchings, we rely on a initial normalisation based on the pattern orientation. A comprehensive study is made using major state-of-the-art shape descriptors over several public datasets of shapes such as graphical symbols (both printed and hand-drawn), handwritten characters and footwear prints. In all tests, the method proves its generic behaviour by providing better recognition performance. Overall, we validate that our method is robust to deformed shape due to distortion, degradation and occlusion.
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DOI: 10.1142/S0218001413500080
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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">10.1142/S0218001413500080</idno><series><title level="j">International Journal of Pattern Recognition and Artificial Intelligence</title><idno type="ISSN">0218-0014</idno><imprint><date type="datePub">2013-03-27</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="mix" xml:lang="en"><term>Dynamic Programming</term><term>Pattern Recognition</term><term>Shape Descriptor</term><term>The Radon Transform</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">In this paper, we present a pattern recognition method that uses dynamic programming (DP) for the alignment of Radon features. The key characteristic of the method is to use dynamic time warping (DTW) to match corresponding pairs of the Radon features for all possible projections. Thanks to DTW, we avoid compressing the feature matrix into a single vector which would otherwise miss information. To reduce the possible number of matchings, we rely on a initial normalisation based on the pattern orientation. A comprehensive study is made using major state-of-the-art shape descriptors over several public datasets of shapes such as graphical symbols (both printed and hand-drawn), handwritten characters and footwear prints. In all tests, the method proves its generic behaviour by providing better recognition performance. Overall, we validate that our method is robust to deformed shape due to distortion, degradation and occlusion.</div></front></TEI><hal api="V3"><titleStmt><title xml:lang="en">DTW-Radon-based Shape Descriptor for Pattern Recognition</title><author role="aut"><persName><forename type="first">Santosh</forename><surname>K.C.</surname></persName><email>kcsantsa@loria.fr</email><idno type="halauthor">446132</idno><affiliation ref="#struct-206042"></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">850871</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-413289"></orgName><affiliation ref="#struct-206044"></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">525576</idno><orgName ref="#struct-301664"></orgName><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">2013-05-20 06:22:12</date><date type="whenModified">2015-09-21 11:21:49</date><date type="whenReleased">2013-05-20 09:26:27</date><date type="whenProduced">2013-03-27</date><date type="whenEndEmbargoed">2013-05-20</date><ref type="file" target="https://hal.inria.fr/hal-00823961/document"><date notBefore="2013-05-20"></date></ref><ref type="file" subtype="author" n="1" target="https://hal.inria.fr/hal-00823961/file/kc_IJPRAI0.pdf"><date notBefore="2013-05-20"></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">hal-00823961</idno><idno type="halUri">https://hal.inria.fr/hal-00823961</idno><idno type="halBibtex">kc:hal-00823961</idno><idno type="halRefHtml">International Journal of Pattern Recognition and Artificial Intelligence, World Scientific Publishing, 2013, 27 (3), <10.1142/S0218001413500080></idno><idno type="halRef">International Journal of Pattern Recognition and Artificial Intelligence, World Scientific Publishing, 2013, 27 (3), <10.1142/S0218001413500080></idno></publicationStmt><seriesStmt><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="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-PARIS5">Université Paris Descartes (Paris 5)</idno><idno type="stamp" n="UNIV-LORRAINE">Université de Lorraine</idno></seriesStmt><notesStmt><note type="audience" n="2">International</note><note type="popular" n="0">No</note><note type="peer" n="1">Yes</note></notesStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">DTW-Radon-based Shape Descriptor for Pattern Recognition</title><author role="aut"><persName><forename type="first">Santosh</forename><surname>K.C.</surname></persName><email>kcsantsa@loria.fr</email><idno type="halAuthorId">446132</idno><affiliation ref="#struct-206042"></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">850871</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-413289"></orgName><affiliation ref="#struct-206044"></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">525576</idno><orgName ref="#struct-301664"></orgName><affiliation ref="#struct-103372"></affiliation></author></analytic><monogr><idno type="halJournalId" status="VALID">14620</idno><idno type="issn">0218-0014</idno><idno type="eissn">0218-0014</idno><title level="j">International Journal of Pattern Recognition and Artificial Intelligence</title><imprint><publisher>World Scientific Publishing</publisher><biblScope unit="volume">27</biblScope><biblScope unit="issue">3</biblScope><date type="datePub">2013-03-27</date></imprint></monogr><idno type="doi">10.1142/S0218001413500080</idno></biblStruct></sourceDesc><profileDesc><langUsage><language ident="en">English</language></langUsage><textClass><keywords scheme="author"><term xml:lang="en">The Radon Transform</term><term xml:lang="en">Dynamic Programming</term><term xml:lang="en">Shape Descriptor</term><term xml:lang="en">Pattern Recognition</term></keywords><classCode scheme="halDomain" n="info.info-cv">Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]</classCode><classCode scheme="halTypology" n="ART">Journal articles</classCode></textClass><abstract xml:lang="en">In this paper, we present a pattern recognition method that uses dynamic programming (DP) for the alignment of Radon features. The key characteristic of the method is to use dynamic time warping (DTW) to match corresponding pairs of the Radon features for all possible projections. Thanks to DTW, we avoid compressing the feature matrix into a single vector which would otherwise miss information. To reduce the possible number of matchings, we rely on a initial normalisation based on the pattern orientation. A comprehensive study is made using major state-of-the-art shape descriptors over several public datasets of shapes such as graphical symbols (both printed and hand-drawn), handwritten characters and footwear prints. In all tests, the method proves its generic behaviour by providing better recognition performance. Overall, we validate that our method is robust to deformed shape due to distortion, degradation and occlusion.</abstract></profileDesc></hal></record>Pour manipuler ce document sous Unix (Dilib)
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