InforLorV4, PascalFrancis, Corpus, bibRecord, 000153

A protocol to characterize the descriptive power and the complementarity of shape descriptors

Identifieur interne : 000153 ( PascalFrancis/Corpus ); précédent : 000152; suivant : 000154

A protocol to characterize the descriptive power and the complementarity of shape descriptors

Auteurs : Muriel Visani ; Oriol Ramos Terrades ; Salvatore Tabbone

Source :

International journal on document analysis and recognition : (Print) [ 1433-2833 ] ; 2011.

RBID : Pascal:11-0227814

Descripteurs français

Pascal (Inist)
- Analyse documentaire, Reconnaissance forme, Base de données, Sémiologie, Symbole, Robustesse, ., Recherche image, Recherche par contenu.

English descriptors

KwdEn :
- Content-based retrieval, Database, Document analysis, Image retrieval, Pattern recognition, Robustness, Semiology, Symbol.

Abstract

Most document analysis applications rely on the extraction of shape descriptors, which may be grouped into different categories, each category having its own advantages and drawbacks (O.R. Terrades et al. in Proceedings of ICDAR'07, pp. 227-231, 2007). In order to improve the richness of their description, many authors choose to combine multiple descriptors. Yet, most of the authors who propose a new descriptor content themselves with comparing its performance to the performance of a set of single state-of-the-art descriptors in a specific applicative context (e.g. symbol recognition, symbol spotting...). This results in a proliferation of the shape descriptors proposed in the literature. In this article, we propose an innovative protocol, the originality of which is to be as independent of the final application as possible and which relies on new quantitative and qualitative measures. We introduce two types of mea- sures: while the measures of the first type are intended to characterize the descriptive power (in terms of uniqueness, distinctiveness and robustness towards noise) of a descriptor, the second type of measures characterizes the complemen- tarity between multiple descriptors. Characterizing upstream the complementarity of shape descriptors is an alternative to the usual approach where the descriptors to be combined are selected by trial and error, considering the performance char- acteristics of the overall system. To illustrate the contribution of this protocol, we performed experimental studies using a set of descriptors and a set of symbols which are widely used by the community namely ART and SC descriptors and the GREC 2003 database.

Notice en format standard (ISO 2709)

Pour connaître la documentation sur le format Inist Standard.

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Format Inist (serveur)

NO :	PASCAL 11-0227814 INIST
ET :	A protocol to characterize the descriptive power and the complementarity of shape descriptors
AU :	VISANI (Muriel); RAMOS TERRADES (Oriol); TABBONE (Salvatore); WENYIN (Liu); VALVENY (Ernest)
AF :	L3I, University of La Rochelle/La Rochelle/France (1 aut.); Instituto Tecnológico de Informatica, Universidad Politécnica de Valencia/Valencia/Espagne (2 aut.); LORIA, University of Nancy 2/Vandoeuvre-les-Nancy/France (3 aut.); City University of Hong Kong/Hong Kong/Chine (1 aut.); Computer Vision Center - Universitat Autònoma de Barcelona, Edifici O, Campus UAB/08193 Bellaterra/Espagne (2 aut.)
DT :	Publication en série; Niveau analytique
SO :	International journal on document analysis and recognition : (Print); ISSN 1433-2833; Allemagne; Da. 2011; Vol. 14; No. 1; Pp. 87-100; Bibl. 30 ref.
LA :	Anglais
EA :	Most document analysis applications rely on the extraction of shape descriptors, which may be grouped into different categories, each category having its own advantages and drawbacks (O.R. Terrades et al. in Proceedings of ICDAR'07, pp. 227-231, 2007). In order to improve the richness of their description, many authors choose to combine multiple descriptors. Yet, most of the authors who propose a new descriptor content themselves with comparing its performance to the performance of a set of single state-of-the-art descriptors in a specific applicative context (e.g. symbol recognition, symbol spotting...). This results in a proliferation of the shape descriptors proposed in the literature. In this article, we propose an innovative protocol, the originality of which is to be as independent of the final application as possible and which relies on new quantitative and qualitative measures. We introduce two types of mea- sures: while the measures of the first type are intended to characterize the descriptive power (in terms of uniqueness, distinctiveness and robustness towards noise) of a descriptor, the second type of measures characterizes the complemen- tarity between multiple descriptors. Characterizing upstream the complementarity of shape descriptors is an alternative to the usual approach where the descriptors to be combined are selected by trial and error, considering the performance char- acteristics of the overall system. To illustrate the contribution of this protocol, we performed experimental studies using a set of descriptors and a set of symbols which are widely used by the community namely ART and SC descriptors and the GREC 2003 database.
CC :	001D02C03
FD :	Analyse documentaire; Reconnaissance forme; Base de données; Sémiologie; Symbole; Robustesse; .; Recherche image; Recherche par contenu
ED :	Document analysis; Pattern recognition; Database; Semiology; Symbol; Robustness; Image retrieval; Content-based retrieval
SD :	Análisis documental; Reconocimiento patrón; Base dato; Semiología; Símbolo; Robustez; Búsqueda de imagen; Búsqueda por Contenidos
LO :	INIST-26790.354000193723420090
ID :	11-0227814

Links to Exploration step

Pascal:11-0227814

Le document en format XML

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<ET>A protocol to characterize the descriptive power and the complementarity of shape descriptors</ET>
<AU>VISANI (Muriel); RAMOS TERRADES (Oriol); TABBONE (Salvatore); WENYIN (Liu); VALVENY (Ernest)</AU>
<AF>L3I, University of La Rochelle/La Rochelle/France (1 aut.); Instituto Tecnológico de Informatica, Universidad Politécnica de Valencia/Valencia/Espagne (2 aut.); LORIA, University of Nancy 2/Vandoeuvre-les-Nancy/France (3 aut.); City University of Hong Kong/Hong Kong/Chine (1 aut.); Computer Vision Center - Universitat Autònoma de Barcelona, Edifici O, Campus UAB/08193 Bellaterra/Espagne (2 aut.)</AF>
<DT>Publication en série; Niveau analytique</DT>
<SO>International journal on document analysis and recognition : (Print); ISSN 1433-2833; Allemagne; Da. 2011; Vol. 14; No. 1; Pp. 87-100; Bibl. 30 ref.</SO>
<LA>Anglais</LA>
<EA>Most document analysis applications rely on the extraction of shape descriptors, which may be grouped into different categories, each category having its own advantages and drawbacks (O.R. Terrades et al. in Proceedings of ICDAR'07, pp. 227-231, 2007). In order to improve the richness of their description, many authors choose to combine multiple descriptors. Yet, most of the authors who propose a new descriptor content themselves with comparing its performance to the performance of a set of single state-of-the-art descriptors in a specific applicative context (e.g. symbol recognition, symbol spotting...). This results in a proliferation of the shape descriptors proposed in the literature. In this article, we propose an innovative protocol, the originality of which is to be as independent of the final application as possible and which relies on new quantitative and qualitative measures. We introduce two types of mea- sures: while the measures of the first type are intended to characterize the descriptive power (in terms of uniqueness, distinctiveness and robustness towards noise) of a descriptor, the second type of measures characterizes the complemen- tarity between multiple descriptors. Characterizing upstream the complementarity of shape descriptors is an alternative to the usual approach where the descriptors to be combined are selected by trial and error, considering the performance char- acteristics of the overall system. To illustrate the contribution of this protocol, we performed experimental studies using a set of descriptors and a set of symbols which are widely used by the community namely ART and SC descriptors and the GREC 2003 database.</EA>
<CC>001D02C03</CC>
<FD>Analyse documentaire; Reconnaissance forme; Base de données; Sémiologie; Symbole; Robustesse; .; Recherche image; Recherche par contenu</FD>
<ED>Document analysis; Pattern recognition; Database; Semiology; Symbol; Robustness; Image retrieval; Content-based retrieval</ED>
<SD>Análisis documental; Reconocimiento patrón; Base dato; Semiología; Símbolo; Robustez; Búsqueda de imagen; Búsqueda por Contenidos</SD>
<LO>INIST-26790.354000193723420090</LO>
<ID>11-0227814</ID>
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A protocol to characterize the descriptive power and the complementarity of shape descriptors

A protocol to characterize the descriptive power and the complementarity of shape descriptors

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