Retrieval of Historical Documents by Word Spotting
Identifieur interne :
000219 ( PascalFrancis/Corpus );
précédent :
000218;
suivant :
000220
Retrieval of Historical Documents by Word Spotting
Auteurs : Nikoleta Doulgeri ;
Ergina KavallieratouSource :
-
Proceedings of SPIE, the International Society for Optical Engineering [ 0277-786X ] ; 2009.
RBID : Pascal:09-0372223
Descripteurs français
- Pascal (Inist)
- Implémentation,
Reconnaissance caractère,
Indexation,
Traitement image document,
Reconnaissance optique caractère,
Requête,
Apprentissage,
Alphabet,
Interpolation,
0130C,
Traitement image,
4230V.
English descriptors
Abstract
The implementation of word spotting is not an easy procedure and it gets even worse in the case of historical documents since it requires character recognition and indexing of the document images. A general technique for word spotting is presented, independent of OCR, using automatic representation of the text queries of the user by word images and comparing them with the word images extracted from the document images. The proposed system does not require training. The only required preprocessing task is the alphabet determination. Global shape features are used to describe the words. They are very general in order to capture the form of the word and appropriately normalized in order to face the usual problems of variance in resolution, width of words and fonts. A novel technique that makes use of the interpolation method is presented. In our experiments, we analyze the system dependence on its parameters and we prove that its performance is similar to the trainable systems.
Notice en format standard (ISO 2709)
Pour connaître la documentation sur le format Inist Standard.
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| A03 | | 1 | | @0 Proc. SPIE Int. Soc. Opt. Eng. |
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| A05 | | | | @2 7247 |
|---|
| A08 | 01 | 1 | ENG | @1 Retrieval of Historical Documents by Word Spotting |
|---|
| A09 | 01 | 1 | ENG | @1 Document recognition and retrieval XVI : 20-22 January 2009, San Jose, California, USA |
|---|
| A11 | 01 | 1 | | @1 DOULGERI (Nikoleta) |
|---|
| A11 | 02 | 1 | | @1 KAVALLIERATOU (Ergina) |
|---|
| A12 | 01 | 1 | | @1 BERKNER (Kathrin) @9 ed. |
|---|
| A12 | 02 | 1 | | @1 LIKFORMAN-SULEM (Laurence) @9 ed. |
|---|
| A14 | 01 | | | @1 University of the Aegean University @2 83200 Samos @3 GRC @Z 1 aut. @Z 2 aut. |
|---|
| A18 | 01 | 1 | | @1 IS & T--the Society for Imaging Science and Technology @3 USA @9 org-cong. |
|---|
| A18 | 02 | 1 | | @1 SPIE @3 USA @9 org-cong. |
|---|
| A18 | 03 | 1 | | @1 Ricoh Innovations @3 INC @9 org-cong. |
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| A20 | | | | @2 724706.1-724706.10 |
|---|
| A21 | | | | @1 2009 |
|---|
| A23 | 01 | | | @0 ENG |
|---|
| A25 | 01 | | | @1 SPIE @2 Bellingham WA |
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| A25 | 02 | | | @1 IS&T @2 Springfield VA |
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| A44 | | | | @0 0000 @1 © 2009 INIST-CNRS. All rights reserved. |
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| A45 | | | | @0 16 ref. |
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| A47 | 01 | 1 | | @0 09-0372223 |
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| A60 | | | | @1 P @2 C |
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| A64 | 01 | 1 | | @0 Proceedings of SPIE, the International Society for Optical Engineering |
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| A66 | 01 | | | @0 USA |
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| C01 | 01 | | ENG | @0 The implementation of word spotting is not an easy procedure and it gets even worse in the case of historical documents since it requires character recognition and indexing of the document images. A general technique for word spotting is presented, independent of OCR, using automatic representation of the text queries of the user by word images and comparing them with the word images extracted from the document images. The proposed system does not require training. The only required preprocessing task is the alphabet determination. Global shape features are used to describe the words. They are very general in order to capture the form of the word and appropriately normalized in order to face the usual problems of variance in resolution, width of words and fonts. A novel technique that makes use of the interpolation method is presented. In our experiments, we analyze the system dependence on its parameters and we prove that its performance is similar to the trainable systems. |
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| C03 | 02 | 3 | FRE | @0 Reconnaissance caractère @5 62 |
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| C03 | 02 | 3 | ENG | @0 Character recognition @5 62 |
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| C03 | 03 | 3 | FRE | @0 Indexation @5 63 |
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| C03 | 03 | 3 | ENG | @0 Indexing @5 63 |
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| C03 | 04 | 3 | FRE | @0 Traitement image document @5 64 |
|---|
| C03 | 04 | 3 | ENG | @0 Document image processing @5 64 |
|---|
| C03 | 05 | 3 | FRE | @0 Reconnaissance optique caractère @5 65 |
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| C03 | 05 | 3 | ENG | @0 Optical character recognition @5 65 |
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| C03 | 06 | X | FRE | @0 Requête @5 66 |
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| C03 | 06 | X | ENG | @0 Query @5 66 |
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| C03 | 06 | X | SPA | @0 Pregunta documental @5 66 |
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| C03 | 07 | 3 | FRE | @0 Apprentissage @5 67 |
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| C03 | 07 | 3 | ENG | @0 Learning @5 67 |
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| C03 | 08 | X | FRE | @0 Alphabet @5 68 |
|---|
| C03 | 08 | X | ENG | @0 Alphabet @5 68 |
|---|
| C03 | 08 | X | SPA | @0 Alfabeto @5 68 |
|---|
| C03 | 09 | 3 | FRE | @0 Interpolation @5 69 |
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| C03 | 09 | 3 | ENG | @0 Interpolation @5 69 |
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| C03 | 10 | 3 | FRE | @0 0130C @4 INC @5 83 |
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| C03 | 11 | 3 | FRE | @0 Traitement image @4 INC @5 84 |
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| pR |
| A30 | 01 | 1 | ENG | @1 Document recognition and retrieval @2 16 @3 San Jose CA USA @4 2009 |
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|
|---|
Format Inist (serveur)
| NO : | PASCAL 09-0372223 INIST |
|---|
| ET : | Retrieval of Historical Documents by Word Spotting |
|---|
| AU : | DOULGERI (Nikoleta); KAVALLIERATOU (Ergina); BERKNER (Kathrin); LIKFORMAN-SULEM (Laurence) |
|---|
| AF : | University of the Aegean University/83200 Samos/Grèce (1 aut., 2 aut.) |
|---|
| DT : | Publication en série; Congrès; Niveau analytique |
|---|
| SO : | Proceedings of SPIE, the International Society for Optical Engineering; ISSN 0277-786X; Coden PSISDG; Etats-Unis; Da. 2009; Vol. 7247; 724706.1-724706.10; Bibl. 16 ref. |
|---|
| LA : | Anglais |
|---|
| EA : | The implementation of word spotting is not an easy procedure and it gets even worse in the case of historical documents since it requires character recognition and indexing of the document images. A general technique for word spotting is presented, independent of OCR, using automatic representation of the text queries of the user by word images and comparing them with the word images extracted from the document images. The proposed system does not require training. The only required preprocessing task is the alphabet determination. Global shape features are used to describe the words. They are very general in order to capture the form of the word and appropriately normalized in order to face the usual problems of variance in resolution, width of words and fonts. A novel technique that makes use of the interpolation method is presented. In our experiments, we analyze the system dependence on its parameters and we prove that its performance is similar to the trainable systems. |
|---|
| CC : | 001B00A30C; 001B40B30V |
|---|
| FD : | Implémentation; Reconnaissance caractère; Indexation; Traitement image document; Reconnaissance optique caractère; Requête; Apprentissage; Alphabet; Interpolation; 0130C; Traitement image; 4230V |
|---|
| ED : | Implementation; Character recognition; Indexing; Document image processing; Optical character recognition; Query; Learning; Alphabet; Interpolation |
|---|
| SD : | Pregunta documental; Alfabeto |
|---|
| LO : | INIST-21760.354000172953960050 |
|---|
| ID : | 09-0372223 |
|---|
Links to Exploration step
Pascal:09-0372223
Le document en format XML
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<ET>Retrieval of Historical Documents by Word Spotting</ET>
<AU>DOULGERI (Nikoleta); KAVALLIERATOU (Ergina); BERKNER (Kathrin); LIKFORMAN-SULEM (Laurence)</AU>
<AF>University of the Aegean University/83200 Samos/Grèce (1 aut., 2 aut.)</AF>
<DT>Publication en série; Congrès; Niveau analytique</DT>
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<LA>Anglais</LA>
<EA>The implementation of word spotting is not an easy procedure and it gets even worse in the case of historical documents since it requires character recognition and indexing of the document images. A general technique for word spotting is presented, independent of OCR, using automatic representation of the text queries of the user by word images and comparing them with the word images extracted from the document images. The proposed system does not require training. The only required preprocessing task is the alphabet determination. Global shape features are used to describe the words. They are very general in order to capture the form of the word and appropriately normalized in order to face the usual problems of variance in resolution, width of words and fonts. A novel technique that makes use of the interpolation method is presented. In our experiments, we analyze the system dependence on its parameters and we prove that its performance is similar to the trainable systems.</EA>
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