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A Local Adaptation of the Histogram Radon Transform Descriptor: An Application to a Shoe Print Dataset

Identifieur interne : 000280 ( Hal/Corpus ); précédent : 000279; suivant : 000281

A Local Adaptation of the Histogram Radon Transform Descriptor: An Application to a Shoe Print Dataset

Auteurs : Makoto Hasegawa ; Salvatore Tabbone

Source :

RBID : Hal:hal-00764901

English descriptors

Abstract

In this paper we propose a shape recognition approach applied to a dataset composed of 512 shoeprints where shapes are strongly occluded. We provide a local adaptation of the HRT (Histogram Radon Transform) descriptor. A shoeprint is decomposed into its connect components and describes locally by the local HRT. Then, following this description, we find the best local matching between the connected components and the similarity between two images is defined as mean of local similarity measures.

Url:
DOI: 10.1007/978-3-642-34166-3_74

Links to Exploration step

Hal:hal-00764901

Le document en format XML

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<title xml:lang="en">A Local Adaptation of the Histogram Radon Transform Descriptor: An Application to a Shoe Print Dataset</title>
<author role="aut">
<persName>
<forename type="first">Makoto</forename>
<surname>Hasegawa</surname>
</persName>
<email>mack.hasegawa@gmail.com</email>
<idno type="halAuthorId">795797</idno>
<affiliation ref="#struct-206044"></affiliation>
</author>
<author role="aut">
<persName>
<forename type="first">Salvatore</forename>
<surname>Tabbone</surname>
</persName>
<email>Antoine.Tabbone@loria.fr</email>
<idno type="halAuthorId">795798</idno>
<orgName ref="#struct-413289"></orgName>
<affiliation ref="#struct-206044"></affiliation>
</author>
</analytic>
<monogr>
<idno type="isbn">978-3-642-34165-6</idno>
<title level="m">Structural, Syntactic, and Statistical Pattern Recognition: Lecture Notes in Computer Science</title>
<editor>Georgy Gimel'farb</editor>
<imprint>
<publisher>Springer</publisher>
<biblScope unit="serie">Lecture Notes in Computer Science</biblScope>
<biblScope unit="volume">7626</biblScope>
<biblScope unit="pp">675-683</biblScope>
<date type="datePub">2012-12-01</date>
</imprint>
</monogr>
<idno type="doi">10.1007/978-3-642-34166-3_74</idno>
<ref type="seeAlso">Joint IAPR International Workshop, SSPR&SPR 2012, Hiroshima, Japan, November 7-9, 2012. Proceedings</ref>
</biblStruct>
</sourceDesc>
<profileDesc>
<langUsage>
<language ident="en">English</language>
</langUsage>
<textClass>
<keywords scheme="author">
<term xml:lang="en">histogram of Radon transform</term>
<term xml:lang="en">Shape matching</term>
<term xml:lang="en">local descriptor</term>
<term xml:lang="en">histogram of Radon transform.</term>
</keywords>
<classCode scheme="halTypology" n="COUV">Book section</classCode>
</textClass>
<abstract xml:lang="en">In this paper we propose a shape recognition approach applied to a dataset composed of 512 shoeprints where shapes are strongly occluded. We provide a local adaptation of the HRT (Histogram Radon Transform) descriptor. A shoeprint is decomposed into its connect components and describes locally by the local HRT. Then, following this description, we find the best local matching between the connected components and the similarity between two images is defined as mean of local similarity measures.</abstract>
</profileDesc>
</hal>
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