OcrV1, PascalFrancis, Corpus, bibRecord, 000451

Automatic table detection in document images

Identifieur interne : 000451 ( PascalFrancis/Corpus ); précédent : 000450; suivant : 000452

Automatic table detection in document images

Auteurs : Basilios Gatos ; Dimitrios Danatsas ; Ioannis Pratikakis ; Stavros J. Perantonis

Source :

Lecture notes in computer science [ 0302-9743 ] ; 2005.

RBID : Pascal:05-0390700

Descripteurs français

Pascal (Inist)
- Fouille donnée, Reconnaissance forme, Mesure automatique, Détecteur image, Représentation graphique, Texte, Reconnaissance caractère, Reconnaissance optique caractère, Collecticiel, Workflow, Détection contour, Caractère manuscrit, Présentation document, Evaluation performance, Chèque bancaire.

English descriptors

KwdEn :
- Automatic measurement, Bank check, Character recognition, Data mining, Document layout, Edge detection, Graphics, Groupware, Image sensor, Manuscript character, Optical character recognition, Pattern recognition, Performance evaluation, Text, Workflow.

Abstract

In this paper, we propose a novel technique for automatic table detection in document images. Lines and tables are among the most frequent graphic, non-textual entities in documents and their detection is directly related to the OCR performance as well as to the document layout description. We propose a workflow for table detection that comprises three distinct steps: (i) image preprocessing; (ii) horizontal and vertical line detection and (iii) table detection. The efficiency of the proposed method is demonstrated by using a performance evaluation scheme which considers a great variety of documents such as forms, newspapers/magazines, scientific journals, tickets/bank cheques, certificates and handwritten documents.

Notice en format standard (ISO 2709)

Pour connaître la documentation sur le format Inist Standard.

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A09	`01`	`1`	`ENG`	`@1 Pattern recognition and data mining : Bath, 22-25 august 2005`
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A11	`04`	`1`		`@1 PERANTONIS (Stavros J.)`
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A30	`01`	`1`	`ENG`	`@1 ICAPR : international conference on advances in pattern recognition @3 Bath GBR @4 2005-08-22`

Format Inist (serveur)

NO :	PASCAL 05-0390700 INIST
ET :	Automatic table detection in document images
AU :	GATOS (Basilios); DANATSAS (Dimitrios); PRATIKAKIS (Ioannis); PERANTONIS (Stavros J.); SINGH (Sameer); SINGH (Maneesha); APTE (Chid); PERNER (Petra)
AF :	Computational Intelligence Laboratory, Institute of Informatics and Telecommunications, National Center for Scientific Research "Demokritos"/15310 Athens/Grèce (1 aut., 2 aut., 3 aut., 4 aut.)
DT :	Publication en série; Congrès; Niveau analytique
SO :	Lecture notes in computer science; ISSN 0302-9743; Allemagne; Da. 2005; Vol. 3686; Part I, 609-618; Bibl. 11 ref.
LA :	Anglais
EA :	In this paper, we propose a novel technique for automatic table detection in document images. Lines and tables are among the most frequent graphic, non-textual entities in documents and their detection is directly related to the OCR performance as well as to the document layout description. We propose a workflow for table detection that comprises three distinct steps: (i) image preprocessing; (ii) horizontal and vertical line detection and (iii) table detection. The efficiency of the proposed method is demonstrated by using a performance evaluation scheme which considers a great variety of documents such as forms, newspapers/magazines, scientific journals, tickets/bank cheques, certificates and handwritten documents.
CC :	001D02B07D; 001D02B07B
FD :	Fouille donnée; Reconnaissance forme; Mesure automatique; Détecteur image; Représentation graphique; Texte; Reconnaissance caractère; Reconnaissance optique caractère; Collecticiel; Workflow; Détection contour; Caractère manuscrit; Présentation document; Evaluation performance; Chèque bancaire
ED :	Data mining; Pattern recognition; Automatic measurement; Image sensor; Graphics; Text; Character recognition; Optical character recognition; Groupware; Workflow; Edge detection; Manuscript character; Document layout; Performance evaluation; Bank check
SD :	Busca dato; Reconocimiento patrón; Medición automática; Detector imagen; Grafo (curva); Texto; Reconocimiento carácter; Reconocimento óptico de caracteres; Groupware; Workflow; Detección contorno; Carácter manuscrito; Presentación documento; Evaluación prestación; Cheque bancario
LO :	INIST-16343.354000124412760670
ID :	05-0390700

Links to Exploration step

Pascal:05-0390700

Le document en format XML

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<fC03 i1="08" i2="X" l="ENG"><s0>Optical character recognition</s0>
<s5>11</s5>
</fC03>
<fC03 i1="08" i2="X" l="SPA"><s0>Reconocimento óptico de caracteres</s0>
<s5>11</s5>
</fC03>
<fC03 i1="09" i2="X" l="FRE"><s0>Collecticiel</s0>
<s5>12</s5>
</fC03>
<fC03 i1="09" i2="X" l="ENG"><s0>Groupware</s0>
<s5>12</s5>
</fC03>
<fC03 i1="09" i2="X" l="SPA"><s0>Groupware</s0>
<s5>12</s5>
</fC03>
<fC03 i1="10" i2="X" l="FRE"><s0>Workflow</s0>
<s5>13</s5>
</fC03>
<fC03 i1="10" i2="X" l="ENG"><s0>Workflow</s0>
<s5>13</s5>
</fC03>
<fC03 i1="10" i2="X" l="SPA"><s0>Workflow</s0>
<s5>13</s5>
</fC03>
<fC03 i1="11" i2="X" l="FRE"><s0>Détection contour</s0>
<s5>14</s5>
</fC03>
<fC03 i1="11" i2="X" l="ENG"><s0>Edge detection</s0>
<s5>14</s5>
</fC03>
<fC03 i1="11" i2="X" l="SPA"><s0>Detección contorno</s0>
<s5>14</s5>
</fC03>
<fC03 i1="12" i2="X" l="FRE"><s0>Caractère manuscrit</s0>
<s5>15</s5>
</fC03>
<fC03 i1="12" i2="X" l="ENG"><s0>Manuscript character</s0>
<s5>15</s5>
</fC03>
<fC03 i1="12" i2="X" l="SPA"><s0>Carácter manuscrito</s0>
<s5>15</s5>
</fC03>
<fC03 i1="13" i2="X" l="FRE"><s0>Présentation document</s0>
<s5>18</s5>
</fC03>
<fC03 i1="13" i2="X" l="ENG"><s0>Document layout</s0>
<s5>18</s5>
</fC03>
<fC03 i1="13" i2="X" l="SPA"><s0>Presentación documento</s0>
<s5>18</s5>
</fC03>
<fC03 i1="14" i2="X" l="FRE"><s0>Evaluation performance</s0>
<s5>19</s5>
</fC03>
<fC03 i1="14" i2="X" l="ENG"><s0>Performance evaluation</s0>
<s5>19</s5>
</fC03>
<fC03 i1="14" i2="X" l="SPA"><s0>Evaluación prestación</s0>
<s5>19</s5>
</fC03>
<fC03 i1="15" i2="X" l="FRE"><s0>Chèque bancaire</s0>
<s5>20</s5>
</fC03>
<fC03 i1="15" i2="X" l="ENG"><s0>Bank check</s0>
<s5>20</s5>
</fC03>
<fC03 i1="15" i2="X" l="SPA"><s0>Cheque bancario</s0>
<s5>20</s5>
</fC03>
<fN21><s1>276</s1>
</fN21>
<fN44 i1="01"><s1>OTO</s1>
</fN44>
<fN82><s1>OTO</s1>
</fN82>
</pA>
<pR><fA30 i1="01" i2="1" l="ENG"><s1>ICAPR : international conference on advances in pattern recognition</s1>
<s3>Bath GBR</s3>
<s4>2005-08-22</s4>
</fA30>
</pR>
</standard>
<server><NO>PASCAL 05-0390700 INIST</NO>
<ET>Automatic table detection in document images</ET>
<AU>GATOS (Basilios); DANATSAS (Dimitrios); PRATIKAKIS (Ioannis); PERANTONIS (Stavros J.); SINGH (Sameer); SINGH (Maneesha); APTE (Chid); PERNER (Petra)</AU>
<AF>Computational Intelligence Laboratory, Institute of Informatics and Telecommunications, National Center for Scientific Research "Demokritos"/15310 Athens/Grèce (1 aut., 2 aut., 3 aut., 4 aut.)</AF>
<DT>Publication en série; Congrès; Niveau analytique</DT>
<SO>Lecture notes in computer science; ISSN 0302-9743; Allemagne; Da. 2005; Vol. 3686; Part I, 609-618; Bibl. 11 ref.</SO>
<LA>Anglais</LA>
<EA>In this paper, we propose a novel technique for automatic table detection in document images. Lines and tables are among the most frequent graphic, non-textual entities in documents and their detection is directly related to the OCR performance as well as to the document layout description. We propose a workflow for table detection that comprises three distinct steps: (i) image preprocessing; (ii) horizontal and vertical line detection and (iii) table detection. The efficiency of the proposed method is demonstrated by using a performance evaluation scheme which considers a great variety of documents such as forms, newspapers/magazines, scientific journals, tickets/bank cheques, certificates and handwritten documents.</EA>
<CC>001D02B07D; 001D02B07B</CC>
<FD>Fouille donnée; Reconnaissance forme; Mesure automatique; Détecteur image; Représentation graphique; Texte; Reconnaissance caractère; Reconnaissance optique caractère; Collecticiel; Workflow; Détection contour; Caractère manuscrit; Présentation document; Evaluation performance; Chèque bancaire</FD>
<ED>Data mining; Pattern recognition; Automatic measurement; Image sensor; Graphics; Text; Character recognition; Optical character recognition; Groupware; Workflow; Edge detection; Manuscript character; Document layout; Performance evaluation; Bank check</ED>
<SD>Busca dato; Reconocimiento patrón; Medición automática; Detector imagen; Grafo (curva); Texto; Reconocimiento carácter; Reconocimento óptico de caracteres; Groupware; Workflow; Detección contorno; Carácter manuscrito; Presentación documento; Evaluación prestación; Cheque bancario</SD>
<LO>INIST-16343.354000124412760670</LO>
<ID>05-0390700</ID>
</server>
</inist>
</record>

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Automatic table detection in document images

Automatic table detection in document images

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