Content-based matching of line-drawing images using the Hough transform
Identifieur interne : 000975 ( PascalFrancis/Corpus ); précédent : 000974; suivant : 000976Content-based matching of line-drawing images using the Hough transform
Auteurs : Pasi Fr Nti ; Alexey Mednonogov ; Ville Kyrki ; Heikki K Lvi InenSource :
- International journal on document analysis and recognition : (Print) [ 1433-2833 ] ; 2000.
Descripteurs français
- Pascal (Inist)
English descriptors
- KwdEn :
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.
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Format Inist (serveur)
NO : | PASCAL 01-0105911 INIST |
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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:01-0105911Le document en format XML
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<front><div type="abstract" xml:lang="en">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.</div>
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<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>
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<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>
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