Shape Recognition Via an a Contrario Model for Size Functions
Identifieur interne :
000340 ( PascalFrancis/Corpus );
précédent :
000339;
suivant :
000341
Shape Recognition Via an a Contrario Model for Size Functions
Auteurs : Andrea Cerri ;
Daniela Giorgi ;
Pablo Muse ;
Frédéric Sur ;
Federico TomassiniSource :
-
Lecture notes in computer science [ 0302-9743 ] ; 2006.
RBID : Pascal:08-0067642
Descripteurs français
- Pascal (Inist)
- Analyse image,
Reconnaissance image,
Reconnaissance forme,
Forme géométrique,
Traitement image,
Similitude,
Raisonnement basé sur cas,
Métrique,
Variabilité,
Mesure probabilité,
Modélisation,
Analyse statistique,
Approche probabiliste.
English descriptors
- KwdEn :
- Case based reasoning,
Geometrical shape,
Image analysis,
Image processing,
Image recognition,
Metric,
Modeling,
Pattern recognition,
Probabilistic approach,
Probability measure,
Similarity,
Statistical analysis,
Variability.
Abstract
Shape recognition methods are often based on feature comparison. When features are of different natures, combining the value of distances or (dis-)similarity measures is not easy since each feature has its own amount of variability. Statistical models are therefore needed. This article proposes a statistical method, namely an a contrario method, to merge features derived from several families of size functions. This merging is usually achieved through a touchy normalizing of the distances. The proposed model consists in building a probability measure. It leads to a global shape recognition method dedicated to perceptual similarities.
Notice en format standard (ISO 2709)
Pour connaître la documentation sur le format Inist Standard.
pA |
A01 | 01 | 1 | | @0 0302-9743 |
---|
A05 | | | | @2 4141 |
---|
A08 | 01 | 1 | ENG | @1 Shape Recognition Via an a Contrario Model for Size Functions |
---|
A09 | 01 | 1 | ENG | @1 Image analysis and recognition. Part I-II : Third international conference, ICIAR 2006, Povoa de Varzim, Portugal, September 18-20, 2006 : proceedings |
---|
A11 | 01 | 1 | | @1 CERRI (Andrea) |
---|
A11 | 02 | 1 | | @1 GIORGI (Daniela) |
---|
A11 | 03 | 1 | | @1 MUSE (Pablo) |
---|
A11 | 04 | 1 | | @1 SUR (Frédéric) |
---|
A11 | 05 | 1 | | @1 TOMASSINI (Federico) |
---|
A12 | 01 | 1 | | @1 CAMPILHO (Aurélio) @9 ed. |
---|
A12 | 02 | 1 | | @1 KAMEL (Mohamed) @9 ed. |
---|
A14 | 01 | | | @1 Dipartimento di Matematica Università di Bologna Piazza di Porta S. Donato, 5 @2 40126 Bologna @3 ITA @Z 1 aut. @Z 2 aut. @Z 5 aut. |
---|
A14 | 02 | | | @1 Centre de Mathématiques et de Leurs Applications École Normale Supérieure de Cachan 61, avenue du président Wilson @2 94235 Cachan @3 FRA @Z 3 aut. |
---|
A14 | 03 | | | @1 Loria & INPL Loria, Campus scientifique BP 239 @2 54506 Vandoeuvre-lès-Nancy @3 FRA @Z 4 aut. |
---|
A20 | | | | @1 410-421 |
---|
A21 | | | | @1 2006 |
---|
A23 | 01 | | | @0 ENG |
---|
A26 | 01 | | | @0 3-540-44891-8 |
---|
A43 | 01 | | | @1 INIST @2 16343 @5 354000172812481200 |
---|
A44 | | | | @0 0000 @1 © 2008 INIST-CNRS. All rights reserved. |
---|
A45 | | | | @0 19 ref. |
---|
A47 | 01 | 1 | | @0 08-0067642 |
---|
A60 | | | | @1 P @2 C |
---|
A61 | | | | @0 A |
---|
A64 | 01 | 1 | | @0 Lecture notes in computer science |
---|
A66 | 01 | | | @0 DEU |
---|
C01 | 01 | | ENG | @0 Shape recognition methods are often based on feature comparison. When features are of different natures, combining the value of distances or (dis-)similarity measures is not easy since each feature has its own amount of variability. Statistical models are therefore needed. This article proposes a statistical method, namely an a contrario method, to merge features derived from several families of size functions. This merging is usually achieved through a touchy normalizing of the distances. The proposed model consists in building a probability measure. It leads to a global shape recognition method dedicated to perceptual similarities. |
---|
C02 | 01 | X | | @0 001D02C03 |
---|
C03 | 01 | X | FRE | @0 Analyse image @5 01 |
---|
C03 | 01 | X | ENG | @0 Image analysis @5 01 |
---|
C03 | 01 | X | SPA | @0 Análisis imagen @5 01 |
---|
C03 | 02 | X | FRE | @0 Reconnaissance image @5 02 |
---|
C03 | 02 | X | ENG | @0 Image recognition @5 02 |
---|
C03 | 02 | X | SPA | @0 Reconocimiento imagen @5 02 |
---|
C03 | 03 | X | FRE | @0 Reconnaissance forme @5 06 |
---|
C03 | 03 | X | ENG | @0 Pattern recognition @5 06 |
---|
C03 | 03 | X | SPA | @0 Reconocimiento patrón @5 06 |
---|
C03 | 04 | X | FRE | @0 Forme géométrique @5 07 |
---|
C03 | 04 | X | ENG | @0 Geometrical shape @5 07 |
---|
C03 | 04 | X | SPA | @0 Forma geométrica @5 07 |
---|
C03 | 05 | X | FRE | @0 Traitement image @5 08 |
---|
C03 | 05 | X | ENG | @0 Image processing @5 08 |
---|
C03 | 05 | X | SPA | @0 Procesamiento imagen @5 08 |
---|
C03 | 06 | X | FRE | @0 Similitude @5 09 |
---|
C03 | 06 | X | ENG | @0 Similarity @5 09 |
---|
C03 | 06 | X | SPA | @0 Similitud @5 09 |
---|
C03 | 07 | X | FRE | @0 Raisonnement basé sur cas @5 18 |
---|
C03 | 07 | X | ENG | @0 Case based reasoning @5 18 |
---|
C03 | 07 | X | SPA | @0 Razonamiento fundado sobre caso @5 18 |
---|
C03 | 08 | X | FRE | @0 Métrique @5 19 |
---|
C03 | 08 | X | ENG | @0 Metric @5 19 |
---|
C03 | 08 | X | SPA | @0 Métrico @5 19 |
---|
C03 | 09 | X | FRE | @0 Variabilité @5 20 |
---|
C03 | 09 | X | ENG | @0 Variability @5 20 |
---|
C03 | 09 | X | SPA | @0 Variabilidad @5 20 |
---|
C03 | 10 | X | FRE | @0 Mesure probabilité @5 21 |
---|
C03 | 10 | X | ENG | @0 Probability measure @5 21 |
---|
C03 | 10 | X | SPA | @0 Medida probabilidad @5 21 |
---|
C03 | 11 | X | FRE | @0 Modélisation @5 23 |
---|
C03 | 11 | X | ENG | @0 Modeling @5 23 |
---|
C03 | 11 | X | SPA | @0 Modelización @5 23 |
---|
C03 | 12 | X | FRE | @0 Analyse statistique @5 24 |
---|
C03 | 12 | X | ENG | @0 Statistical analysis @5 24 |
---|
C03 | 12 | X | SPA | @0 Análisis estadístico @5 24 |
---|
C03 | 13 | X | FRE | @0 Approche probabiliste @5 25 |
---|
C03 | 13 | X | ENG | @0 Probabilistic approach @5 25 |
---|
C03 | 13 | X | SPA | @0 Enfoque probabilista @5 25 |
---|
N21 | | | | @1 035 |
---|
N44 | 01 | | | @1 OTO |
---|
N82 | | | | @1 OTO |
---|
|
pR |
A30 | 01 | 1 | ENG | @1 ICIAR 2006 @2 3 @3 Povoa de Varzim PRT @4 2006 |
---|
|
Format Inist (serveur)
NO : | PASCAL 08-0067642 INIST |
ET : | Shape Recognition Via an a Contrario Model for Size Functions |
AU : | CERRI (Andrea); GIORGI (Daniela); MUSE (Pablo); SUR (Frédéric); TOMASSINI (Federico); CAMPILHO (Aurélio); KAMEL (Mohamed) |
AF : | Dipartimento di Matematica Università di Bologna Piazza di Porta S. Donato, 5/40126 Bologna/Italie (1 aut., 2 aut., 5 aut.); Centre de Mathématiques et de Leurs Applications École Normale Supérieure de Cachan 61, avenue du président Wilson/94235 Cachan/France (3 aut.); Loria & INPL Loria, Campus scientifique BP 239/54506 Vandoeuvre-lès-Nancy/France (4 aut.) |
DT : | Publication en série; Congrès; Niveau analytique |
SO : | Lecture notes in computer science; ISSN 0302-9743; Allemagne; Da. 2006; Vol. 4141; Pp. 410-421; Bibl. 19 ref. |
LA : | Anglais |
EA : | Shape recognition methods are often based on feature comparison. When features are of different natures, combining the value of distances or (dis-)similarity measures is not easy since each feature has its own amount of variability. Statistical models are therefore needed. This article proposes a statistical method, namely an a contrario method, to merge features derived from several families of size functions. This merging is usually achieved through a touchy normalizing of the distances. The proposed model consists in building a probability measure. It leads to a global shape recognition method dedicated to perceptual similarities. |
CC : | 001D02C03 |
FD : | Analyse image; Reconnaissance image; Reconnaissance forme; Forme géométrique; Traitement image; Similitude; Raisonnement basé sur cas; Métrique; Variabilité; Mesure probabilité; Modélisation; Analyse statistique; Approche probabiliste |
ED : | Image analysis; Image recognition; Pattern recognition; Geometrical shape; Image processing; Similarity; Case based reasoning; Metric; Variability; Probability measure; Modeling; Statistical analysis; Probabilistic approach |
SD : | Análisis imagen; Reconocimiento imagen; Reconocimiento patrón; Forma geométrica; Procesamiento imagen; Similitud; Razonamiento fundado sobre caso; Métrico; Variabilidad; Medida probabilidad; Modelización; Análisis estadístico; Enfoque probabilista |
LO : | INIST-16343.354000172812481200 |
ID : | 08-0067642 |
Links to Exploration step
Pascal:08-0067642
Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en" level="a">Shape Recognition Via an a Contrario Model for Size Functions</title>
<author><name sortKey="Cerri, Andrea" sort="Cerri, Andrea" uniqKey="Cerri A" first="Andrea" last="Cerri">Andrea Cerri</name>
<affiliation><inist:fA14 i1="01"><s1>Dipartimento di Matematica Università di Bologna Piazza di Porta S. Donato, 5</s1>
<s2>40126 Bologna</s2>
<s3>ITA</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
<sZ>5 aut.</sZ>
</inist:fA14>
</affiliation>
</author>
<author><name sortKey="Giorgi, Daniela" sort="Giorgi, Daniela" uniqKey="Giorgi D" first="Daniela" last="Giorgi">Daniela Giorgi</name>
<affiliation><inist:fA14 i1="01"><s1>Dipartimento di Matematica Università di Bologna Piazza di Porta S. Donato, 5</s1>
<s2>40126 Bologna</s2>
<s3>ITA</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
<sZ>5 aut.</sZ>
</inist:fA14>
</affiliation>
</author>
<author><name sortKey="Muse, Pablo" sort="Muse, Pablo" uniqKey="Muse P" first="Pablo" last="Muse">Pablo Muse</name>
<affiliation><inist:fA14 i1="02"><s1>Centre de Mathématiques et de Leurs Applications École Normale Supérieure de Cachan 61, avenue du président Wilson</s1>
<s2>94235 Cachan</s2>
<s3>FRA</s3>
<sZ>3 aut.</sZ>
</inist:fA14>
</affiliation>
</author>
<author><name sortKey="Sur, Frederic" sort="Sur, Frederic" uniqKey="Sur F" first="Frédéric" last="Sur">Frédéric Sur</name>
<affiliation><inist:fA14 i1="03"><s1>Loria & INPL Loria, Campus scientifique BP 239</s1>
<s2>54506 Vandoeuvre-lès-Nancy</s2>
<s3>FRA</s3>
<sZ>4 aut.</sZ>
</inist:fA14>
</affiliation>
</author>
<author><name sortKey="Tomassini, Federico" sort="Tomassini, Federico" uniqKey="Tomassini F" first="Federico" last="Tomassini">Federico Tomassini</name>
<affiliation><inist:fA14 i1="01"><s1>Dipartimento di Matematica Università di Bologna Piazza di Porta S. Donato, 5</s1>
<s2>40126 Bologna</s2>
<s3>ITA</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
<sZ>5 aut.</sZ>
</inist:fA14>
</affiliation>
</author>
</titleStmt>
<publicationStmt><idno type="wicri:source">INIST</idno>
<idno type="inist">08-0067642</idno>
<date when="2006">2006</date>
<idno type="stanalyst">PASCAL 08-0067642 INIST</idno>
<idno type="RBID">Pascal:08-0067642</idno>
<idno type="wicri:Area/PascalFrancis/Corpus">000340</idno>
</publicationStmt>
<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a">Shape Recognition Via an a Contrario Model for Size Functions</title>
<author><name sortKey="Cerri, Andrea" sort="Cerri, Andrea" uniqKey="Cerri A" first="Andrea" last="Cerri">Andrea Cerri</name>
<affiliation><inist:fA14 i1="01"><s1>Dipartimento di Matematica Università di Bologna Piazza di Porta S. Donato, 5</s1>
<s2>40126 Bologna</s2>
<s3>ITA</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
<sZ>5 aut.</sZ>
</inist:fA14>
</affiliation>
</author>
<author><name sortKey="Giorgi, Daniela" sort="Giorgi, Daniela" uniqKey="Giorgi D" first="Daniela" last="Giorgi">Daniela Giorgi</name>
<affiliation><inist:fA14 i1="01"><s1>Dipartimento di Matematica Università di Bologna Piazza di Porta S. Donato, 5</s1>
<s2>40126 Bologna</s2>
<s3>ITA</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
<sZ>5 aut.</sZ>
</inist:fA14>
</affiliation>
</author>
<author><name sortKey="Muse, Pablo" sort="Muse, Pablo" uniqKey="Muse P" first="Pablo" last="Muse">Pablo Muse</name>
<affiliation><inist:fA14 i1="02"><s1>Centre de Mathématiques et de Leurs Applications École Normale Supérieure de Cachan 61, avenue du président Wilson</s1>
<s2>94235 Cachan</s2>
<s3>FRA</s3>
<sZ>3 aut.</sZ>
</inist:fA14>
</affiliation>
</author>
<author><name sortKey="Sur, Frederic" sort="Sur, Frederic" uniqKey="Sur F" first="Frédéric" last="Sur">Frédéric Sur</name>
<affiliation><inist:fA14 i1="03"><s1>Loria & INPL Loria, Campus scientifique BP 239</s1>
<s2>54506 Vandoeuvre-lès-Nancy</s2>
<s3>FRA</s3>
<sZ>4 aut.</sZ>
</inist:fA14>
</affiliation>
</author>
<author><name sortKey="Tomassini, Federico" sort="Tomassini, Federico" uniqKey="Tomassini F" first="Federico" last="Tomassini">Federico Tomassini</name>
<affiliation><inist:fA14 i1="01"><s1>Dipartimento di Matematica Università di Bologna Piazza di Porta S. Donato, 5</s1>
<s2>40126 Bologna</s2>
<s3>ITA</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
<sZ>5 aut.</sZ>
</inist:fA14>
</affiliation>
</author>
</analytic>
<series><title level="j" type="main">Lecture notes in computer science</title>
<idno type="ISSN">0302-9743</idno>
<imprint><date when="2006">2006</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
<seriesStmt><title level="j" type="main">Lecture notes in computer science</title>
<idno type="ISSN">0302-9743</idno>
</seriesStmt>
</fileDesc>
<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Case based reasoning</term>
<term>Geometrical shape</term>
<term>Image analysis</term>
<term>Image processing</term>
<term>Image recognition</term>
<term>Metric</term>
<term>Modeling</term>
<term>Pattern recognition</term>
<term>Probabilistic approach</term>
<term>Probability measure</term>
<term>Similarity</term>
<term>Statistical analysis</term>
<term>Variability</term>
</keywords>
<keywords scheme="Pascal" xml:lang="fr"><term>Analyse image</term>
<term>Reconnaissance image</term>
<term>Reconnaissance forme</term>
<term>Forme géométrique</term>
<term>Traitement image</term>
<term>Similitude</term>
<term>Raisonnement basé sur cas</term>
<term>Métrique</term>
<term>Variabilité</term>
<term>Mesure probabilité</term>
<term>Modélisation</term>
<term>Analyse statistique</term>
<term>Approche probabiliste</term>
</keywords>
</textClass>
</profileDesc>
</teiHeader>
<front><div type="abstract" xml:lang="en">Shape recognition methods are often based on feature comparison. When features are of different natures, combining the value of distances or (dis-)similarity measures is not easy since each feature has its own amount of variability. Statistical models are therefore needed. This article proposes a statistical method, namely an a contrario method, to merge features derived from several families of size functions. This merging is usually achieved through a touchy normalizing of the distances. The proposed model consists in building a probability measure. It leads to a global shape recognition method dedicated to perceptual similarities.</div>
</front>
</TEI>
<inist><standard h6="B"><pA><fA01 i1="01" i2="1"><s0>0302-9743</s0>
</fA01>
<fA05><s2>4141</s2>
</fA05>
<fA08 i1="01" i2="1" l="ENG"><s1>Shape Recognition Via an a Contrario Model for Size Functions</s1>
</fA08>
<fA09 i1="01" i2="1" l="ENG"><s1>Image analysis and recognition. Part I-II : Third international conference, ICIAR 2006, Povoa de Varzim, Portugal, September 18-20, 2006 : proceedings</s1>
</fA09>
<fA11 i1="01" i2="1"><s1>CERRI (Andrea)</s1>
</fA11>
<fA11 i1="02" i2="1"><s1>GIORGI (Daniela)</s1>
</fA11>
<fA11 i1="03" i2="1"><s1>MUSE (Pablo)</s1>
</fA11>
<fA11 i1="04" i2="1"><s1>SUR (Frédéric)</s1>
</fA11>
<fA11 i1="05" i2="1"><s1>TOMASSINI (Federico)</s1>
</fA11>
<fA12 i1="01" i2="1"><s1>CAMPILHO (Aurélio)</s1>
<s9>ed.</s9>
</fA12>
<fA12 i1="02" i2="1"><s1>KAMEL (Mohamed)</s1>
<s9>ed.</s9>
</fA12>
<fA14 i1="01"><s1>Dipartimento di Matematica Università di Bologna Piazza di Porta S. Donato, 5</s1>
<s2>40126 Bologna</s2>
<s3>ITA</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
<sZ>5 aut.</sZ>
</fA14>
<fA14 i1="02"><s1>Centre de Mathématiques et de Leurs Applications École Normale Supérieure de Cachan 61, avenue du président Wilson</s1>
<s2>94235 Cachan</s2>
<s3>FRA</s3>
<sZ>3 aut.</sZ>
</fA14>
<fA14 i1="03"><s1>Loria & INPL Loria, Campus scientifique BP 239</s1>
<s2>54506 Vandoeuvre-lès-Nancy</s2>
<s3>FRA</s3>
<sZ>4 aut.</sZ>
</fA14>
<fA20><s1>410-421</s1>
</fA20>
<fA21><s1>2006</s1>
</fA21>
<fA23 i1="01"><s0>ENG</s0>
</fA23>
<fA26 i1="01"><s0>3-540-44891-8</s0>
</fA26>
<fA43 i1="01"><s1>INIST</s1>
<s2>16343</s2>
<s5>354000172812481200</s5>
</fA43>
<fA44><s0>0000</s0>
<s1>© 2008 INIST-CNRS. All rights reserved.</s1>
</fA44>
<fA45><s0>19 ref.</s0>
</fA45>
<fA47 i1="01" i2="1"><s0>08-0067642</s0>
</fA47>
<fA60><s1>P</s1>
<s2>C</s2>
</fA60>
<fA64 i1="01" i2="1"><s0>Lecture notes in computer science</s0>
</fA64>
<fA66 i1="01"><s0>DEU</s0>
</fA66>
<fC01 i1="01" l="ENG"><s0>Shape recognition methods are often based on feature comparison. When features are of different natures, combining the value of distances or (dis-)similarity measures is not easy since each feature has its own amount of variability. Statistical models are therefore needed. This article proposes a statistical method, namely an a contrario method, to merge features derived from several families of size functions. This merging is usually achieved through a touchy normalizing of the distances. The proposed model consists in building a probability measure. It leads to a global shape recognition method dedicated to perceptual similarities.</s0>
</fC01>
<fC02 i1="01" i2="X"><s0>001D02C03</s0>
</fC02>
<fC03 i1="01" i2="X" l="FRE"><s0>Analyse image</s0>
<s5>01</s5>
</fC03>
<fC03 i1="01" i2="X" l="ENG"><s0>Image analysis</s0>
<s5>01</s5>
</fC03>
<fC03 i1="01" i2="X" l="SPA"><s0>Análisis imagen</s0>
<s5>01</s5>
</fC03>
<fC03 i1="02" i2="X" l="FRE"><s0>Reconnaissance image</s0>
<s5>02</s5>
</fC03>
<fC03 i1="02" i2="X" l="ENG"><s0>Image recognition</s0>
<s5>02</s5>
</fC03>
<fC03 i1="02" i2="X" l="SPA"><s0>Reconocimiento imagen</s0>
<s5>02</s5>
</fC03>
<fC03 i1="03" i2="X" l="FRE"><s0>Reconnaissance forme</s0>
<s5>06</s5>
</fC03>
<fC03 i1="03" i2="X" l="ENG"><s0>Pattern recognition</s0>
<s5>06</s5>
</fC03>
<fC03 i1="03" i2="X" l="SPA"><s0>Reconocimiento patrón</s0>
<s5>06</s5>
</fC03>
<fC03 i1="04" i2="X" l="FRE"><s0>Forme géométrique</s0>
<s5>07</s5>
</fC03>
<fC03 i1="04" i2="X" l="ENG"><s0>Geometrical shape</s0>
<s5>07</s5>
</fC03>
<fC03 i1="04" i2="X" l="SPA"><s0>Forma geométrica</s0>
<s5>07</s5>
</fC03>
<fC03 i1="05" i2="X" l="FRE"><s0>Traitement image</s0>
<s5>08</s5>
</fC03>
<fC03 i1="05" i2="X" l="ENG"><s0>Image processing</s0>
<s5>08</s5>
</fC03>
<fC03 i1="05" i2="X" l="SPA"><s0>Procesamiento imagen</s0>
<s5>08</s5>
</fC03>
<fC03 i1="06" i2="X" l="FRE"><s0>Similitude</s0>
<s5>09</s5>
</fC03>
<fC03 i1="06" i2="X" l="ENG"><s0>Similarity</s0>
<s5>09</s5>
</fC03>
<fC03 i1="06" i2="X" l="SPA"><s0>Similitud</s0>
<s5>09</s5>
</fC03>
<fC03 i1="07" i2="X" l="FRE"><s0>Raisonnement basé sur cas</s0>
<s5>18</s5>
</fC03>
<fC03 i1="07" i2="X" l="ENG"><s0>Case based reasoning</s0>
<s5>18</s5>
</fC03>
<fC03 i1="07" i2="X" l="SPA"><s0>Razonamiento fundado sobre caso</s0>
<s5>18</s5>
</fC03>
<fC03 i1="08" i2="X" l="FRE"><s0>Métrique</s0>
<s5>19</s5>
</fC03>
<fC03 i1="08" i2="X" l="ENG"><s0>Metric</s0>
<s5>19</s5>
</fC03>
<fC03 i1="08" i2="X" l="SPA"><s0>Métrico</s0>
<s5>19</s5>
</fC03>
<fC03 i1="09" i2="X" l="FRE"><s0>Variabilité</s0>
<s5>20</s5>
</fC03>
<fC03 i1="09" i2="X" l="ENG"><s0>Variability</s0>
<s5>20</s5>
</fC03>
<fC03 i1="09" i2="X" l="SPA"><s0>Variabilidad</s0>
<s5>20</s5>
</fC03>
<fC03 i1="10" i2="X" l="FRE"><s0>Mesure probabilité</s0>
<s5>21</s5>
</fC03>
<fC03 i1="10" i2="X" l="ENG"><s0>Probability measure</s0>
<s5>21</s5>
</fC03>
<fC03 i1="10" i2="X" l="SPA"><s0>Medida probabilidad</s0>
<s5>21</s5>
</fC03>
<fC03 i1="11" i2="X" l="FRE"><s0>Modélisation</s0>
<s5>23</s5>
</fC03>
<fC03 i1="11" i2="X" l="ENG"><s0>Modeling</s0>
<s5>23</s5>
</fC03>
<fC03 i1="11" i2="X" l="SPA"><s0>Modelización</s0>
<s5>23</s5>
</fC03>
<fC03 i1="12" i2="X" l="FRE"><s0>Analyse statistique</s0>
<s5>24</s5>
</fC03>
<fC03 i1="12" i2="X" l="ENG"><s0>Statistical analysis</s0>
<s5>24</s5>
</fC03>
<fC03 i1="12" i2="X" l="SPA"><s0>Análisis estadístico</s0>
<s5>24</s5>
</fC03>
<fC03 i1="13" i2="X" l="FRE"><s0>Approche probabiliste</s0>
<s5>25</s5>
</fC03>
<fC03 i1="13" i2="X" l="ENG"><s0>Probabilistic approach</s0>
<s5>25</s5>
</fC03>
<fC03 i1="13" i2="X" l="SPA"><s0>Enfoque probabilista</s0>
<s5>25</s5>
</fC03>
<fN21><s1>035</s1>
</fN21>
<fN44 i1="01"><s1>OTO</s1>
</fN44>
<fN82><s1>OTO</s1>
</fN82>
</pA>
<pR><fA30 i1="01" i2="1" l="ENG"><s1>ICIAR 2006</s1>
<s2>3</s2>
<s3>Povoa de Varzim PRT</s3>
<s4>2006</s4>
</fA30>
</pR>
</standard>
<server><NO>PASCAL 08-0067642 INIST</NO>
<ET>Shape Recognition Via an a Contrario Model for Size Functions</ET>
<AU>CERRI (Andrea); GIORGI (Daniela); MUSE (Pablo); SUR (Frédéric); TOMASSINI (Federico); CAMPILHO (Aurélio); KAMEL (Mohamed)</AU>
<AF>Dipartimento di Matematica Università di Bologna Piazza di Porta S. Donato, 5/40126 Bologna/Italie (1 aut., 2 aut., 5 aut.); Centre de Mathématiques et de Leurs Applications École Normale Supérieure de Cachan 61, avenue du président Wilson/94235 Cachan/France (3 aut.); Loria & INPL Loria, Campus scientifique BP 239/54506 Vandoeuvre-lès-Nancy/France (4 aut.)</AF>
<DT>Publication en série; Congrès; Niveau analytique</DT>
<SO>Lecture notes in computer science; ISSN 0302-9743; Allemagne; Da. 2006; Vol. 4141; Pp. 410-421; Bibl. 19 ref.</SO>
<LA>Anglais</LA>
<EA>Shape recognition methods are often based on feature comparison. When features are of different natures, combining the value of distances or (dis-)similarity measures is not easy since each feature has its own amount of variability. Statistical models are therefore needed. This article proposes a statistical method, namely an a contrario method, to merge features derived from several families of size functions. This merging is usually achieved through a touchy normalizing of the distances. The proposed model consists in building a probability measure. It leads to a global shape recognition method dedicated to perceptual similarities.</EA>
<CC>001D02C03</CC>
<FD>Analyse image; Reconnaissance image; Reconnaissance forme; Forme géométrique; Traitement image; Similitude; Raisonnement basé sur cas; Métrique; Variabilité; Mesure probabilité; Modélisation; Analyse statistique; Approche probabiliste</FD>
<ED>Image analysis; Image recognition; Pattern recognition; Geometrical shape; Image processing; Similarity; Case based reasoning; Metric; Variability; Probability measure; Modeling; Statistical analysis; Probabilistic approach</ED>
<SD>Análisis imagen; Reconocimiento imagen; Reconocimiento patrón; Forma geométrica; Procesamiento imagen; Similitud; Razonamiento fundado sobre caso; Métrico; Variabilidad; Medida probabilidad; Modelización; Análisis estadístico; Enfoque probabilista</SD>
<LO>INIST-16343.354000172812481200</LO>
<ID>08-0067642</ID>
</server>
</inist>
</record>
Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Wicri/Lorraine/explor/InforLorV4/Data/PascalFrancis/Corpus
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000340 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/PascalFrancis/Corpus/biblio.hfd -nk 000340 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien
|wiki= Wicri/Lorraine
|area= InforLorV4
|flux= PascalFrancis
|étape= Corpus
|type= RBID
|clé= Pascal:08-0067642
|texte= Shape Recognition Via an a Contrario Model for Size Functions
}}
| This area was generated with Dilib version V0.6.33. Data generation: Mon Jun 10 21:56:28 2019. Site generation: Fri Feb 25 15:29:27 2022 | ![](Common/icons/LogoDilib.gif) |