Offline recognition of syntax-constrained cursive handwritten text
Identifieur interne :
000761 ( PascalFrancis/Corpus );
précédent :
000760;
suivant :
000762
Offline recognition of syntax-constrained cursive handwritten text
Auteurs : J. Gonzalez ;
I. Salvador ;
A. H. Toselli ;
A. Juan ;
E. Vidal ;
F. CasacubertaSource :
-
Lecture notes in computer science [ 0302-9743 ] ; 2000.
RBID : Pascal:00-0499456
Descripteurs français
English descriptors
Abstract
The problem of continuous handwritten text (CHT) recognition using standard continuous speech recognition technology is considered. Main advantages of this approach are a) system development is completely based on well understood training techniques and b) no segmentation of sentence or line images into characters or words is required, neither in the training nor in the recognition phases. Many recent papers address this problem in a similar way. Our work aims at contributing to this trend in two main aspects: i) We focus on the recognition of individual, isolated characters using the very same technology as for CHT recognition in order to tune essential representation parameters. The results are themselves interesting since they are comparable with state-of-the-art results on the same standard OCR database. And ii) all the work (except for the image processing and feature extraction steps) is strictly based on a well known and widely available standard toolkit for continuous speech recognition.
Notice en format standard (ISO 2709)
Pour connaître la documentation sur le format Inist Standard.
| pA |
| A01 | 01 | 1 | | @0 0302-9743 |
|---|
| A05 | | | | @2 1876 |
|---|
| A08 | 01 | 1 | ENG | @1 Offline recognition of syntax-constrained cursive handwritten text |
|---|
| A09 | 01 | 1 | ENG | @1 Advances in pattern recognition : Alicante, 30 August - 1 September 2000 |
|---|
| A11 | 01 | 1 | | @1 GONZALEZ (J.) |
|---|
| A11 | 02 | 1 | | @1 SALVADOR (I.) |
|---|
| A11 | 03 | 1 | | @1 TOSELLI (A. H.) |
|---|
| A11 | 04 | 1 | | @1 JUAN (A.) |
|---|
| A11 | 05 | 1 | | @1 VIDAL (E.) |
|---|
| A11 | 06 | 1 | | @1 CASACUBERTA (F.) |
|---|
| A12 | 01 | 1 | | @1 FERRI (Francesc J.) @9 ed. |
|---|
| A12 | 02 | 1 | | @1 INESTA (José M.) @9 ed. |
|---|
| A12 | 03 | 1 | | @1 ADNAN AMIN @9 ed. |
|---|
| A12 | 04 | 1 | | @1 PUDIL (Pavel) @9 ed. |
|---|
| A14 | 01 | | | @1 Instituto Tecnológico de Informàtica, Universidad Politécnica de Valencia, Camino de Vera s/n @2 46071 Valencia @3 ESP @Z 1 aut. @Z 2 aut. @Z 3 aut. @Z 4 aut. @Z 5 aut. @Z 6 aut. |
|---|
| A20 | | | | @1 143-153 |
|---|
| A21 | | | | @1 2000 |
|---|
| A23 | 01 | | | @0 ENG |
|---|
| A26 | 01 | | | @0 3-540-67946-4 |
|---|
| A43 | 01 | | | @1 INIST @2 16343 @5 354000090087160150 |
|---|
| A44 | | | | @0 0000 @1 © 2000 INIST-CNRS. All rights reserved. |
|---|
| A45 | | | | @0 11 ref. |
|---|
| A47 | 01 | 1 | | @0 00-0499456 |
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| A60 | | | | @1 P @2 C |
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| A61 | | | | @0 A |
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| A64 | 01 | 1 | | @0 Lecture notes in computer science |
|---|
| A66 | 01 | | | @0 DEU |
|---|
| A66 | 02 | | | @0 USA |
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| C01 | 01 | | ENG | @0 The problem of continuous handwritten text (CHT) recognition using standard continuous speech recognition technology is considered. Main advantages of this approach are a) system development is completely based on well understood training techniques and b) no segmentation of sentence or line images into characters or words is required, neither in the training nor in the recognition phases. Many recent papers address this problem in a similar way. Our work aims at contributing to this trend in two main aspects: i) We focus on the recognition of individual, isolated characters using the very same technology as for CHT recognition in order to tune essential representation parameters. The results are themselves interesting since they are comparable with state-of-the-art results on the same standard OCR database. And ii) all the work (except for the image processing and feature extraction steps) is strictly based on a well known and widely available standard toolkit for continuous speech recognition. |
|---|
| C02 | 01 | X | | @0 001D02C03 |
|---|
| C03 | 01 | X | FRE | @0 Ecriture @5 01 |
|---|
| C03 | 01 | X | ENG | @0 Hand writing @5 01 |
|---|
| C03 | 01 | X | SPA | @0 Escritura manual @5 01 |
|---|
| C03 | 02 | X | FRE | @0 Extraction forme @5 02 |
|---|
| C03 | 02 | X | ENG | @0 Pattern extraction @5 02 |
|---|
| C03 | 02 | X | SPA | @0 Extracción forma @5 02 |
|---|
| C03 | 03 | X | FRE | @0 Reconnaissance caractère @5 03 |
|---|
| C03 | 03 | X | ENG | @0 Character recognition @5 03 |
|---|
| C03 | 03 | X | SPA | @0 Reconocimiento carácter @5 03 |
|---|
| C03 | 04 | X | FRE | @0 Caractère manuscrit @5 04 |
|---|
| C03 | 04 | X | ENG | @0 Manuscript character @5 04 |
|---|
| C03 | 04 | X | SPA | @0 Carácter manuscrito @5 04 |
|---|
| C03 | 05 | X | FRE | @0 Modélisation @5 05 |
|---|
| C03 | 05 | X | ENG | @0 Modeling @5 05 |
|---|
| C03 | 05 | X | SPA | @0 Modelización @5 05 |
|---|
| C03 | 06 | X | FRE | @0 Reconnaissance optique caractère @5 06 |
|---|
| C03 | 06 | X | ENG | @0 Optical character recognition @5 06 |
|---|
| C03 | 06 | X | SPA | @0 Reconocimento óptico de caracteres @5 06 |
|---|
| C03 | 07 | X | FRE | @0 Texte @5 07 |
|---|
| C03 | 07 | X | ENG | @0 Text @5 07 |
|---|
| C03 | 07 | X | SPA | @0 Texto @5 07 |
|---|
| N21 | | | | @1 332 |
|---|
|
|---|
| pR |
| A30 | 01 | 1 | ENG | @1 Joint IAPR international workshops SSPR 2000 and SPR 2000 @3 Alicante ESP @4 2000-08-30 |
|---|
|
|---|
Format Inist (serveur)
| NO : | PASCAL 00-0499456 INIST |
|---|
| ET : | Offline recognition of syntax-constrained cursive handwritten text |
|---|
| AU : | GONZALEZ (J.); SALVADOR (I.); TOSELLI (A. H.); JUAN (A.); VIDAL (E.); CASACUBERTA (F.); FERRI (Francesc J.); INESTA (José M.); ADNAN AMIN; PUDIL (Pavel) |
|---|
| AF : | Instituto Tecnológico de Informàtica, Universidad Politécnica de Valencia, Camino de Vera s/n/46071 Valencia/Espagne (1 aut., 2 aut., 3 aut., 4 aut., 5 aut., 6 aut.) |
|---|
| DT : | Publication en série; Congrès; Niveau analytique |
|---|
| SO : | Lecture notes in computer science; ISSN 0302-9743; Allemagne; Da. 2000; Vol. 1876; Pp. 143-153; Bibl. 11 ref. |
|---|
| LA : | Anglais |
|---|
| EA : | The problem of continuous handwritten text (CHT) recognition using standard continuous speech recognition technology is considered. Main advantages of this approach are a) system development is completely based on well understood training techniques and b) no segmentation of sentence or line images into characters or words is required, neither in the training nor in the recognition phases. Many recent papers address this problem in a similar way. Our work aims at contributing to this trend in two main aspects: i) We focus on the recognition of individual, isolated characters using the very same technology as for CHT recognition in order to tune essential representation parameters. The results are themselves interesting since they are comparable with state-of-the-art results on the same standard OCR database. And ii) all the work (except for the image processing and feature extraction steps) is strictly based on a well known and widely available standard toolkit for continuous speech recognition. |
|---|
| CC : | 001D02C03 |
|---|
| FD : | Ecriture; Extraction forme; Reconnaissance caractère; Caractère manuscrit; Modélisation; Reconnaissance optique caractère; Texte |
|---|
| ED : | Hand writing; Pattern extraction; Character recognition; Manuscript character; Modeling; Optical character recognition; Text |
|---|
| SD : | Escritura manual; Extracción forma; Reconocimiento carácter; Carácter manuscrito; Modelización; Reconocimento óptico de caracteres; Texto |
|---|
| LO : | INIST-16343.354000090087160150 |
|---|
| ID : | 00-0499456 |
|---|
Links to Exploration step
Pascal:00-0499456
Le document en format XML
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</seriesStmt><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Character recognition</term>
<term>Hand writing</term>
<term>Manuscript character</term>
<term>Modeling</term>
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<term>Pattern extraction</term>
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</keywords><front><div type="abstract" xml:lang="en">The problem of continuous handwritten text (CHT) recognition using standard continuous speech recognition technology is considered. Main advantages of this approach are a) system development is completely based on well understood training techniques and b) no segmentation of sentence or line images into characters or words is required, neither in the training nor in the recognition phases. Many recent papers address this problem in a similar way. Our work aims at contributing to this trend in two main aspects: i) We focus on the recognition of individual, isolated characters using the very same technology as for CHT recognition in order to tune essential representation parameters. The results are themselves interesting since they are comparable with state-of-the-art results on the same standard OCR database. And ii) all the work (except for the image processing and feature extraction steps) is strictly based on a well known and widely available standard toolkit for continuous speech recognition.</div>
</front><inist><standard h6="B"><pA><fA01 i1="01" i2="1"><s0>0302-9743</s0>
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</fA08><fA09 i1="01" i2="1" l="ENG"><s1>Advances in pattern recognition : Alicante, 30 August - 1 September 2000</s1>
</fA09><fA11 i1="01" i2="1"><s1>GONZALEZ (J.)</s1>
</fA11><fA11 i1="02" i2="1"><s1>SALVADOR (I.)</s1>
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</fA11><fA11 i1="04" i2="1"><s1>JUAN (A.)</s1>
</fA11><fA11 i1="05" i2="1"><s1>VIDAL (E.)</s1>
</fA11><fA11 i1="06" i2="1"><s1>CASACUBERTA (F.)</s1>
</fA11><fA12 i1="01" i2="1"><s1>FERRI (Francesc J.)</s1>
<s9>ed.</s9>
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</fA12><fA12 i1="03" i2="1"><s1>ADNAN AMIN</s1>
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</fA12><fA12 i1="04" i2="1"><s1>PUDIL (Pavel)</s1>
<s9>ed.</s9>
</fA12><fA14 i1="01"><s1>Instituto Tecnológico de Informàtica, Universidad Politécnica de Valencia, Camino de Vera s/n</s1>
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</fA66><fC01 i1="01" l="ENG"><s0>The problem of continuous handwritten text (CHT) recognition using standard continuous speech recognition technology is considered. Main advantages of this approach are a) system development is completely based on well understood training techniques and b) no segmentation of sentence or line images into characters or words is required, neither in the training nor in the recognition phases. Many recent papers address this problem in a similar way. Our work aims at contributing to this trend in two main aspects: i) We focus on the recognition of individual, isolated characters using the very same technology as for CHT recognition in order to tune essential representation parameters. The results are themselves interesting since they are comparable with state-of-the-art results on the same standard OCR database. And ii) all the work (except for the image processing and feature extraction steps) is strictly based on a well known and widely available standard toolkit for continuous speech recognition.</s0>
</fC01><fC02 i1="01" i2="X"><s0>001D02C03</s0>
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<s5>01</s5>
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<s5>03</s5>
</fC03><fC03 i1="03" i2="X" l="SPA"><s0>Reconocimiento carácter</s0>
<s5>03</s5>
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<s5>04</s5>
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<s5>04</s5>
</fC03><fC03 i1="05" i2="X" l="FRE"><s0>Modélisation</s0>
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<s5>07</s5>
</fC03><fN21><s1>332</s1>
</fN21><pR><fA30 i1="01" i2="1" l="ENG"><s1>Joint IAPR international workshops SSPR 2000 and SPR 2000</s1>
<s3>Alicante ESP</s3>
<s4>2000-08-30</s4>
</fA30><server><NO>PASCAL 00-0499456 INIST</NO>
<ET>Offline recognition of syntax-constrained cursive handwritten text</ET>
<AU>GONZALEZ (J.); SALVADOR (I.); TOSELLI (A. H.); JUAN (A.); VIDAL (E.); CASACUBERTA (F.); FERRI (Francesc J.); INESTA (José M.); ADNAN AMIN; PUDIL (Pavel)</AU>
<AF>Instituto Tecnológico de Informàtica, Universidad Politécnica de Valencia, Camino de Vera s/n/46071 Valencia/Espagne (1 aut., 2 aut., 3 aut., 4 aut., 5 aut., 6 aut.)</AF>
<DT>Publication en série; Congrès; Niveau analytique</DT>
<SO>Lecture notes in computer science; ISSN 0302-9743; Allemagne; Da. 2000; Vol. 1876; Pp. 143-153; Bibl. 11 ref.</SO>
<LA>Anglais</LA>
<EA>The problem of continuous handwritten text (CHT) recognition using standard continuous speech recognition technology is considered. Main advantages of this approach are a) system development is completely based on well understood training techniques and b) no segmentation of sentence or line images into characters or words is required, neither in the training nor in the recognition phases. Many recent papers address this problem in a similar way. Our work aims at contributing to this trend in two main aspects: i) We focus on the recognition of individual, isolated characters using the very same technology as for CHT recognition in order to tune essential representation parameters. The results are themselves interesting since they are comparable with state-of-the-art results on the same standard OCR database. And ii) all the work (except for the image processing and feature extraction steps) is strictly based on a well known and widely available standard toolkit for continuous speech recognition.</EA>
<CC>001D02C03</CC>
<FD>Ecriture; Extraction forme; Reconnaissance caractère; Caractère manuscrit; Modélisation; Reconnaissance optique caractère; Texte</FD>
<ED>Hand writing; Pattern extraction; Character recognition; Manuscript character; Modeling; Optical character recognition; Text</ED>
<SD>Escritura manual; Extracción forma; Reconocimiento carácter; Carácter manuscrito; Modelización; Reconocimento óptico de caracteres; Texto</SD>
<LO>INIST-16343.354000090087160150</LO>
<ID>00-0499456</ID>
</server>
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