InforLorV4, PascalFrancis, Corpus, bibRecord, 000975

Content-based matching of line-drawing images using the Hough transform

Identifieur interne : 000975 ( PascalFrancis/Corpus ); précédent : 000974; suivant : 000976

Content-based matching of line-drawing images using the Hough transform

Auteurs : Pasi Fr Nti ; Alexey Mednonogov ; Ville Kyrki ; Heikki K Lvi Inen

Source :

International journal on document analysis and recognition : (Print) [ 1433-2833 ] ; 2000.

RBID : Pascal:01-0105911

Descripteurs français

Pascal (Inist)
- Appariement image, Information positionnelle, Invariant, Rotation, Accumulateur, Méthode vectorielle, Transformation Hough, Etirage, Reconnaissance graphique, Graphe ligne, Recherche basée contenu.

English descriptors

KwdEn :
- Accumulator, Drawing, Graphical recognition, Hough transformation, Image matching, Invariant, Line graph, Positional information, Rotation, Vector method.

Abstract

We introduce two novel methods for content-based matching of line-drawing images. The methods are based on the Hough transform (HT), which is used to extract global line features in an image. The parameter space of the HT is first thresholded in order to preserve only the most significant values. In the first method, a feature vector is constructed by summing up the significant coefficients in each column of the accumulator matrix. In this way, only the angular information is used. This approach enables simple implementation of scale, translation, and rotation invariant matching. The second variant also includes positional information of the lines and gives a more representative description of the images. Therefore, it achieves more accurate image matching at the cost of more running time.

Notice en format standard (ISO 2709)

Pour connaître la documentation sur le format Inist Standard.

A01	`01`	`1`		`@0 1433-2833`
A03		`1`		`@0 Int. j. doc. anal. recognit. : (Print)`
A05				`@2 3`
A06				`@2 2`
A08	`01`	`1`	`ENG`	`@1 Content-based matching of line-drawing images using the Hough transform`
A09	`01`	`1`	`ENG`	`@1 Special issue on graphics recognition`
A11	`01`	`1`		`@1 FRÄNTI (Pasi)`
A11	`02`	`1`		`@1 MEDNONOGOV (Alexey)`
A11	`03`	`1`		`@1 KYRKI (Ville)`
A11	`04`	`1`		`@1 KÄLVIÄINEN (Heikki)`
A12	`01`	`1`		`@1 CHHABRA (Atul K.) @9 ed.`
A12	`02`	`1`		`@1 DORI (Dov) @9 ed.`
A12	`03`	`1`		`@1 TOMBRE (Karl) @9 ed.`
A14	`01`			`@1 Department of Computer Science, University of Joensuu, P.O. Box 111 @2 80101 Joensuu @3 FIN @Z 1 aut.`
A14	`02`			`@1 Department of Information Technology, Lappeenranta University of Technology, P.O. Box 20 @2 53851 Lappeenranta @3 FIN @Z 2 aut. @Z 3 aut. @Z 4 aut.`
A15	`01`			`@1 Bell Atlantic Network Systems, Advanced Technologies @2 White Plains, NY @3 USA @Z 1 aut.`
A15	`02`			`@1 Technion, Israel Institute of Technology @2 Haifa @3 ISR @Z 2 aut.`
A15	`03`			`@1 LORIA-INPL, Campus scientifique, BP 239 @2 54506 Vandoeuvre-lès-Nancy @3 FRA @Z 3 aut.`
A20				`@1 117-124`
A21				`@1 2000`
A23	`01`			`@0 ENG`
A43	`01`			`@1 INIST @2 26790 @5 354000093660070060`
A44				`@0 0000 @1 © 2001 INIST-CNRS. All rights reserved.`
A45				`@0 26 ref.`
A47	`01`	`1`		`@0 01-0105911`
A60				`@1 P`
A61				`@0 A`
A64	`01`	`1`		`@0 International journal on document analysis and recognition : (Print)`
A66	`01`			`@0 DEU`
C01	`01`		`ENG`	@0 We introduce two novel methods for content-based matching of line-drawing images. The methods are based on the Hough transform (HT), which is used to extract global line features in an image. The parameter space of the HT is first thresholded in order to preserve only the most significant values. In the first method, a feature vector is constructed by summing up the significant coefficients in each column of the accumulator matrix. In this way, only the angular information is used. This approach enables simple implementation of scale, translation, and rotation invariant matching. The second variant also includes positional information of the lines and gives a more representative description of the images. Therefore, it achieves more accurate image matching at the cost of more running time.
C02	`01`	`X`		`@0 001D02C03`
C03	`01`	`3`	`FRE`	`@0 Appariement image @5 01`
C03	`01`	`3`	`ENG`	`@0 Image matching @5 01`
C03	`02`	`X`	`FRE`	`@0 Information positionnelle @5 02`
C03	`02`	`X`	`ENG`	`@0 Positional information @5 02`
C03	`02`	`X`	`SPA`	`@0 Información posicional @5 02`
C03	`03`	`X`	`FRE`	`@0 Invariant @5 03`
C03	`03`	`X`	`ENG`	`@0 Invariant @5 03`
C03	`03`	`X`	`SPA`	`@0 Invariante @5 03`
C03	`04`	`X`	`FRE`	`@0 Rotation @5 04`
C03	`04`	`X`	`ENG`	`@0 Rotation @5 04`
C03	`04`	`X`	`SPA`	`@0 Rotación @5 04`
C03	`05`	`X`	`FRE`	`@0 Accumulateur @5 05`
C03	`05`	`X`	`ENG`	`@0 Accumulator @5 05`
C03	`05`	`X`	`SPA`	`@0 Acumulador @5 05`
C03	`06`	`X`	`FRE`	`@0 Méthode vectorielle @5 06`
C03	`06`	`X`	`ENG`	`@0 Vector method @5 06`
C03	`06`	`X`	`SPA`	`@0 Método vectorial @5 06`
C03	`07`	`X`	`FRE`	`@0 Transformation Hough @5 07`
C03	`07`	`X`	`ENG`	`@0 Hough transformation @5 07`
C03	`07`	`X`	`SPA`	`@0 Transformación Hough @5 07`
C03	`08`	`X`	`FRE`	`@0 Etirage @5 08`
C03	`08`	`X`	`ENG`	`@0 Drawing @5 08`
C03	`08`	`X`	`SPA`	`@0 Estiramiento @5 08`
C03	`09`	`X`	`FRE`	`@0 Reconnaissance graphique @5 09`
C03	`09`	`X`	`ENG`	`@0 Graphical recognition @5 09`
C03	`09`	`X`	`SPA`	`@0 Reconocimiento gráfico @5 09`
C03	`10`	`X`	`FRE`	`@0 Graphe ligne @5 10`
C03	`10`	`X`	`ENG`	`@0 Line graph @5 10`
C03	`10`	`X`	`SPA`	`@0 Grafo línea @5 10`
C03	`11`	`X`	`FRE`	`@0 Recherche basée contenu @4 INC @5 82`
N21				`@1 071`

Format Inist (serveur)

NO :	PASCAL 01-0105911 INIST
ET :	Content-based matching of line-drawing images using the Hough transform
AU :	FRÄNTI (Pasi); MEDNONOGOV (Alexey); KYRKI (Ville); KÄLVIÄINEN (Heikki); CHHABRA (Atul K.); DORI (Dov); TOMBRE (Karl)
AF :	Department of Computer Science, University of Joensuu, P.O. Box 111/80101 Joensuu/Finlande (1 aut.); Department of Information Technology, Lappeenranta University of Technology, P.O. Box 20/53851 Lappeenranta/Finlande (2 aut., 3 aut., 4 aut.); Bell Atlantic Network Systems, Advanced Technologies/White Plains, NY/Etats-Unis (1 aut.); Technion, Israel Institute of Technology/Haifa/Israël (2 aut.); LORIA-INPL, Campus scientifique, BP 239/54506 Vandoeuvre-lès-Nancy/France (3 aut.)
DT :	Publication en série; Niveau analytique
SO :	International journal on document analysis and recognition : (Print); ISSN 1433-2833; Allemagne; Da. 2000; Vol. 3; No. 2; Pp. 117-124; Bibl. 26 ref.
LA :	Anglais
EA :	We introduce two novel methods for content-based matching of line-drawing images. The methods are based on the Hough transform (HT), which is used to extract global line features in an image. The parameter space of the HT is first thresholded in order to preserve only the most significant values. In the first method, a feature vector is constructed by summing up the significant coefficients in each column of the accumulator matrix. In this way, only the angular information is used. This approach enables simple implementation of scale, translation, and rotation invariant matching. The second variant also includes positional information of the lines and gives a more representative description of the images. Therefore, it achieves more accurate image matching at the cost of more running time.
CC :	001D02C03
FD :	Appariement image; Information positionnelle; Invariant; Rotation; Accumulateur; Méthode vectorielle; Transformation Hough; Etirage; Reconnaissance graphique; Graphe ligne; Recherche basée contenu
ED :	Image matching; Positional information; Invariant; Rotation; Accumulator; Vector method; Hough transformation; Drawing; Graphical recognition; Line graph
SD :	Información posicional; Invariante; Rotación; Acumulador; Método vectorial; Transformación Hough; Estiramiento; Reconocimiento gráfico; Grafo línea
LO :	INIST-26790.354000093660070060
ID :	01-0105911

Links to Exploration step

Pascal:01-0105911

Le document en format XML

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<fC01 i1="01" l="ENG"><s0>We introduce two novel methods for content-based matching of line-drawing images. The methods are based on the Hough transform (HT), which is used to extract global line features in an image. The parameter space of the HT is first thresholded in order to preserve only the most significant values. In the first method, a feature vector is constructed by summing up the significant coefficients in each column of the accumulator matrix. In this way, only the angular information is used. This approach enables simple implementation of scale, translation, and rotation invariant matching. The second variant also includes positional information of the lines and gives a more representative description of the images. Therefore, it achieves more accurate image matching at the cost of more running time.</s0>
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<server><NO>PASCAL 01-0105911 INIST</NO>
<ET>Content-based matching of line-drawing images using the Hough transform</ET>
<AU>FRÄNTI (Pasi); MEDNONOGOV (Alexey); KYRKI (Ville); KÄLVIÄINEN (Heikki); CHHABRA (Atul K.); DORI (Dov); TOMBRE (Karl)</AU>
<AF>Department of Computer Science, University of Joensuu, P.O. Box 111/80101 Joensuu/Finlande (1 aut.); Department of Information Technology, Lappeenranta University of Technology, P.O. Box 20/53851 Lappeenranta/Finlande (2 aut., 3 aut., 4 aut.); Bell Atlantic Network Systems, Advanced Technologies/White Plains, NY/Etats-Unis (1 aut.); Technion, Israel Institute of Technology/Haifa/Israël (2 aut.); LORIA-INPL, Campus scientifique, BP 239/54506 Vandoeuvre-lès-Nancy/France (3 aut.)</AF>
<DT>Publication en série; Niveau analytique</DT>
<SO>International journal on document analysis and recognition : (Print); ISSN 1433-2833; Allemagne; Da. 2000; Vol. 3; No. 2; Pp. 117-124; Bibl. 26 ref.</SO>
<LA>Anglais</LA>
<EA>We introduce two novel methods for content-based matching of line-drawing images. The methods are based on the Hough transform (HT), which is used to extract global line features in an image. The parameter space of the HT is first thresholded in order to preserve only the most significant values. In the first method, a feature vector is constructed by summing up the significant coefficients in each column of the accumulator matrix. In this way, only the angular information is used. This approach enables simple implementation of scale, translation, and rotation invariant matching. The second variant also includes positional information of the lines and gives a more representative description of the images. Therefore, it achieves more accurate image matching at the cost of more running time.</EA>
<CC>001D02C03</CC>
<FD>Appariement image; Information positionnelle; Invariant; Rotation; Accumulateur; Méthode vectorielle; Transformation Hough; Etirage; Reconnaissance graphique; Graphe ligne; Recherche basée contenu</FD>
<ED>Image matching; Positional information; Invariant; Rotation; Accumulator; Vector method; Hough transformation; Drawing; Graphical recognition; Line graph</ED>
<SD>Información posicional; Invariante; Rotación; Acumulador; Método vectorial; Transformación Hough; Estiramiento; Reconocimiento gráfico; Grafo línea</SD>
<LO>INIST-26790.354000093660070060</LO>
<ID>01-0105911</ID>
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Content-based matching of line-drawing images using the Hough transform

Content-based matching of line-drawing images using the Hough transform

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