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 |
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| A05 | | | | @2 4141 |
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| A08 | 01 | 1 | ENG | @1 Shape Recognition Via an a Contrario Model for Size Functions |
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| 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) |
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| A11 | 02 | 1 | | @1 GIORGI (Daniela) |
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| A11 | 03 | 1 | | @1 MUSE (Pablo) |
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| A11 | 04 | 1 | | @1 SUR (Frédéric) |
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| A11 | 05 | 1 | | @1 TOMASSINI (Federico) |
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| A12 | 01 | 1 | | @1 CAMPILHO (Aurélio) @9 ed. |
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| A12 | 02 | 1 | | @1 KAMEL (Mohamed) @9 ed. |
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| 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. |
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| A14 | 03 | | | @1 Loria & INPL Loria, Campus scientifique BP 239 @2 54506 Vandoeuvre-lès-Nancy @3 FRA @Z 4 aut. |
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| A20 | | | | @1 410-421 |
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| A21 | | | | @1 2006 |
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| A23 | 01 | | | @0 ENG |
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| A26 | 01 | | | @0 3-540-44891-8 |
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| A44 | | | | @0 0000 @1 © 2008 INIST-CNRS. All rights reserved. |
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| A45 | | | | @0 19 ref. |
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| A60 | | | | @1 P @2 C |
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| A66 | 01 | | | @0 DEU |
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| 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. |
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| C02 | 01 | X | | @0 001D02C03 |
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| C03 | 01 | X | FRE | @0 Analyse image @5 01 |
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| C03 | 01 | X | ENG | @0 Image analysis @5 01 |
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| C03 | 01 | X | SPA | @0 Análisis imagen @5 01 |
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| C03 | 02 | X | FRE | @0 Reconnaissance image @5 02 |
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| C03 | 02 | X | ENG | @0 Image recognition @5 02 |
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| C03 | 02 | X | SPA | @0 Reconocimiento imagen @5 02 |
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| C03 | 03 | X | FRE | @0 Reconnaissance forme @5 06 |
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| 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 |
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| C03 | 04 | X | ENG | @0 Geometrical shape @5 07 |
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| C03 | 04 | X | SPA | @0 Forma geométrica @5 07 |
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| C03 | 05 | X | SPA | @0 Procesamiento imagen @5 08 |
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| C03 | 06 | X | FRE | @0 Similitude @5 09 |
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| C03 | 06 | X | ENG | @0 Similarity @5 09 |
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| C03 | 06 | X | SPA | @0 Similitud @5 09 |
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| C03 | 07 | X | ENG | @0 Case based reasoning @5 18 |
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| C03 | 07 | X | SPA | @0 Razonamiento fundado sobre caso @5 18 |
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| C03 | 08 | X | ENG | @0 Metric @5 19 |
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| C03 | 09 | X | FRE | @0 Variabilité @5 20 |
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| C03 | 09 | X | ENG | @0 Variability @5 20 |
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| C03 | 09 | X | SPA | @0 Variabilidad @5 20 |
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| C03 | 10 | X | FRE | @0 Mesure probabilité @5 21 |
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| C03 | 10 | X | ENG | @0 Probability measure @5 21 |
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| C03 | 10 | X | SPA | @0 Medida probabilidad @5 21 |
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| C03 | 11 | X | FRE | @0 Modélisation @5 23 |
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| C03 | 11 | X | ENG | @0 Modeling @5 23 |
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| C03 | 12 | X | FRE | @0 Analyse statistique @5 24 |
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| C03 | 12 | X | ENG | @0 Statistical analysis @5 24 |
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| pR |
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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
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<term>Metric</term>
<term>Modeling</term>
<term>Pattern recognition</term>
<term>Probabilistic approach</term>
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<term>Similarity</term>
<term>Statistical analysis</term>
<term>Variability</term>
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<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>
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</keywords><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>
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</fA12><fA14 i1="01"><s1>Dipartimento di Matematica Università di Bologna Piazza di Porta S. Donato, 5</s1>
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<s2>54506 Vandoeuvre-lès-Nancy</s2>
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<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><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><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>
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