DTW-Radon-based Shape Descriptor for Pattern Recognition
Identifieur interne : 001266 ( Main/Exploration ); précédent : 001265; suivant : 001267DTW-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.
Url:
DOI: 10.1142/S0218001413500080
Affiliations:
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Le document en format XML
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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><affiliations><list><country><li>France</li></country><region><li>Grand Est</li><li>Lorraine (région)</li></region><settlement><li>Metz</li><li>Nancy</li></settlement><orgName><li>Université de Lorraine</li></orgName></list><tree><country name="France"><region name="Grand Est"><name sortKey="K C, Santosh" sort="K C, Santosh" uniqKey="K C S" first="Santosh" last="K. C.">Santosh K. C.</name></region><name sortKey="Lamiroy, Bart" sort="Lamiroy, Bart" uniqKey="Lamiroy B" first="Bart" last="Lamiroy">Bart Lamiroy</name><name sortKey="Wendling, Laurent" sort="Wendling, Laurent" uniqKey="Wendling L" first="Laurent" last="Wendling">Laurent Wendling</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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