JBIG2 text image compression based on OCR
Identifieur interne :
000332 ( PascalFrancis/Corpus );
précédent :
000331;
suivant :
000333
JBIG2 text image compression based on OCR
Auteurs : JUNQING SHANG ;
CHANGSONG LIU ;
XIAOQING DINGSource :
-
Proceedings of SPIE, the International Society for Optical Engineering [ 0277-786X ] ; 2006.
RBID : Pascal:07-0377973
Descripteurs français
- Pascal (Inist)
- Codage image,
Algorithme,
Etude expérimentale,
Qualité image,
Compression image,
Compression donnée,
Reconnaissance optique caractère,
Concordance forme,
Milieu dissipatif,
Désadaptation,
Taux compression,
Circuit sans perte,
Mesure phase,
0705P,
4230S.
English descriptors
- KwdEn :
- Algorithms,
Compression ratio,
Data compression,
Experimental study,
Image coding,
Image compression,
Image quality,
Lossless circuit,
Lossy medium,
Mismatching,
Optical character recognition,
Pattern matching,
Phase measurement.
Abstract
The JBIG2 (joint bi-level image group) standard for bi-level image coding is drafted to allow encoder designs by individuals. In JBIG2, text images are compressed by pattern matching techniques. In this paper, we propose a lossy text image compression method based on OCR (optical character recognition) which compresses bi-level images into the JBIG2 format. By processing text images with OCR, we can obtain recognition results of characters and the confidence of these results. A representative symbol image could be generated for similar character image blocks by OCR results, sizes of blocks and mismatches between blocks. This symbol image could replace all the similar image blocks and thus a high compression ratio could be achieved. Experiment results show that our algorithm achieves improvements of 75.86% over lossless SPM and 14.05% over lossy PM&S in Latin Character images, and 37.9% over lossless SPM and 4.97% over lossy PM&S in Chinese character images. Our algorithm leads to much fewer substitution errors than previous lossy PM&S and thus preserves acceptable decoded image quality.
Notice en format standard (ISO 2709)
Pour connaître la documentation sur le format Inist Standard.
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| A01 | 01 | 1 | | @0 0277-786X |
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| A05 | | | | @2 6067 |
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| A08 | 01 | 1 | ENG | @1 JBIG2 text image compression based on OCR |
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| A09 | 01 | 1 | ENG | @1 Document recognition and retrieval XIII : 18-19 January 2006, San Jose, California, USA |
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| A11 | 01 | 1 | | @1 JUNQING SHANG |
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| A11 | 02 | 1 | | @1 CHANGSONG LIU |
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| A11 | 03 | 1 | | @1 XIAOQING DING |
|---|
| A12 | 01 | 1 | | @1 TAGHVA (Kazem) @9 ed. |
|---|
| A12 | 02 | 1 | | @1 LIN (Xiaofan) @9 ed. |
|---|
| A14 | 01 | | | @1 State Key Laboratory of Intelligent Technology and Systems Department of Electronic Engineering, Tsinghua University @2 Beijing, 100084 @3 CHN @Z 1 aut. @Z 2 aut. @Z 3 aut. |
|---|
| A18 | 01 | 1 | | @1 IS&T--The Society for Imaging Science and Technology @3 USA @9 org-cong. |
|---|
| A18 | 02 | 1 | | @1 Society of photo-optical instrumentation engineers @3 USA @9 org-cong. |
|---|
| A20 | | | | @2 60670D.1-60670D.12 |
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| A21 | | | | @1 2006 |
|---|
| A23 | 01 | | | @0 ENG |
|---|
| A26 | 01 | | | @0 0-8194-6107-5 |
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| A43 | 01 | | | @1 INIST @2 21760 @5 354000153562240120 |
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| A44 | | | | @0 0000 @1 © 2007 INIST-CNRS. All rights reserved. |
|---|
| A45 | | | | @0 13 ref. |
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| A47 | 01 | 1 | | @0 07-0377973 |
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| A60 | | | | @1 P @2 C |
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| A61 | | | | @0 A |
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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 JBIG2 (joint bi-level image group) standard for bi-level image coding is drafted to allow encoder designs by individuals. In JBIG2, text images are compressed by pattern matching techniques. In this paper, we propose a lossy text image compression method based on OCR (optical character recognition) which compresses bi-level images into the JBIG2 format. By processing text images with OCR, we can obtain recognition results of characters and the confidence of these results. A representative symbol image could be generated for similar character image blocks by OCR results, sizes of blocks and mismatches between blocks. This symbol image could replace all the similar image blocks and thus a high compression ratio could be achieved. Experiment results show that our algorithm achieves improvements of 75.86% over lossless SPM and 14.05% over lossy PM&S in Latin Character images, and 37.9% over lossless SPM and 4.97% over lossy PM&S in Chinese character images. Our algorithm leads to much fewer substitution errors than previous lossy PM&S and thus preserves acceptable decoded image quality. |
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| C03 | 01 | 3 | FRE | @0 Codage image @5 03 |
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| C03 | 01 | 3 | ENG | @0 Image coding @5 03 |
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| C03 | 02 | 3 | FRE | @0 Algorithme @5 23 |
|---|
| C03 | 02 | 3 | ENG | @0 Algorithms @5 23 |
|---|
| C03 | 03 | 3 | FRE | @0 Etude expérimentale @5 30 |
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| C03 | 03 | 3 | ENG | @0 Experimental study @5 30 |
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| C03 | 04 | X | FRE | @0 Qualité image @5 41 |
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| C03 | 04 | X | ENG | @0 Image quality @5 41 |
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| C03 | 04 | X | SPA | @0 Calidad imagen @5 41 |
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| C03 | 05 | X | FRE | @0 Compression image @5 61 |
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| C03 | 05 | X | ENG | @0 Image compression @5 61 |
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| C03 | 05 | X | SPA | @0 Compresión imagen @5 61 |
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| C03 | 06 | 3 | FRE | @0 Compression donnée @5 62 |
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| C03 | 06 | 3 | ENG | @0 Data compression @5 62 |
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| C03 | 07 | 3 | FRE | @0 Reconnaissance optique caractère @5 63 |
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| C03 | 07 | 3 | ENG | @0 Optical character recognition @5 63 |
|---|
| C03 | 08 | 3 | FRE | @0 Concordance forme @5 64 |
|---|
| C03 | 08 | 3 | ENG | @0 Pattern matching @5 64 |
|---|
| C03 | 09 | X | FRE | @0 Milieu dissipatif @5 65 |
|---|
| C03 | 09 | X | ENG | @0 Lossy medium @5 65 |
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| C03 | 09 | X | SPA | @0 Medio dispersor @5 65 |
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| C03 | 10 | X | FRE | @0 Désadaptation @5 66 |
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| C03 | 10 | X | ENG | @0 Mismatching @5 66 |
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| C03 | 10 | X | SPA | @0 Desadaptación @5 66 |
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| C03 | 11 | 3 | FRE | @0 Taux compression @5 67 |
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| C03 | 11 | 3 | ENG | @0 Compression ratio @5 67 |
|---|
| C03 | 12 | X | FRE | @0 Circuit sans perte @5 68 |
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| C03 | 12 | X | ENG | @0 Lossless circuit @5 68 |
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| C03 | 12 | X | SPA | @0 Circuito sin pérdida @5 68 |
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| C03 | 13 | 3 | FRE | @0 Mesure phase @5 69 |
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| C03 | 13 | 3 | ENG | @0 Phase measurement @5 69 |
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| C03 | 14 | 3 | FRE | @0 0705P @4 INC @5 83 |
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| C03 | 15 | 3 | FRE | @0 4230S @4 INC @5 84 |
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| pR |
| A30 | 01 | 1 | ENG | @1 Document recognition and retrieval @2 13 @3 USA @4 2006 |
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Format Inist (serveur)
| NO : | PASCAL 07-0377973 INIST |
|---|
| ET : | JBIG2 text image compression based on OCR |
|---|
| AU : | JUNQING SHANG; CHANGSONG LIU; XIAOQING DING; TAGHVA (Kazem); LIN (Xiaofan) |
|---|
| AF : | State Key Laboratory of Intelligent Technology and Systems Department of Electronic Engineering, Tsinghua University/Beijing, 100084/Chine (1 aut., 2 aut., 3 aut.) |
|---|
| DT : | Publication en série; Congrès; Niveau analytique |
|---|
| SO : | Proceedings of SPIE, the International Society for Optical Engineering; ISSN 0277-786X; Etats-Unis; Da. 2006; Vol. 6067; 60670D.1-60670D.12; Bibl. 13 ref. |
|---|
| LA : | Anglais |
|---|
| EA : | The JBIG2 (joint bi-level image group) standard for bi-level image coding is drafted to allow encoder designs by individuals. In JBIG2, text images are compressed by pattern matching techniques. In this paper, we propose a lossy text image compression method based on OCR (optical character recognition) which compresses bi-level images into the JBIG2 format. By processing text images with OCR, we can obtain recognition results of characters and the confidence of these results. A representative symbol image could be generated for similar character image blocks by OCR results, sizes of blocks and mismatches between blocks. This symbol image could replace all the similar image blocks and thus a high compression ratio could be achieved. Experiment results show that our algorithm achieves improvements of 75.86% over lossless SPM and 14.05% over lossy PM&S in Latin Character images, and 37.9% over lossless SPM and 4.97% over lossy PM&S in Chinese character images. Our algorithm leads to much fewer substitution errors than previous lossy PM&S and thus preserves acceptable decoded image quality. |
|---|
| CC : | 001B00G05P; 001B40B30S; 001D04A04B; 001D04A05A |
|---|
| FD : | Codage image; Algorithme; Etude expérimentale; Qualité image; Compression image; Compression donnée; Reconnaissance optique caractère; Concordance forme; Milieu dissipatif; Désadaptation; Taux compression; Circuit sans perte; Mesure phase; 0705P; 4230S |
|---|
| ED : | Image coding; Algorithms; Experimental study; Image quality; Image compression; Data compression; Optical character recognition; Pattern matching; Lossy medium; Mismatching; Compression ratio; Lossless circuit; Phase measurement |
|---|
| SD : | Calidad imagen; Compresión imagen; Medio dispersor; Desadaptación; Circuito sin pérdida |
|---|
| LO : | INIST-21760.354000153562240120 |
|---|
| ID : | 07-0377973 |
|---|
Links to Exploration step
Pascal:07-0377973
Le document en format XML
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</seriesStmt><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Algorithms</term>
<term>Compression ratio</term>
<term>Data compression</term>
<term>Experimental study</term>
<term>Image coding</term>
<term>Image compression</term>
<term>Image quality</term>
<term>Lossless circuit</term>
<term>Lossy medium</term>
<term>Mismatching</term>
<term>Optical character recognition</term>
<term>Pattern matching</term>
<term>Phase measurement</term>
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<term>Algorithme</term>
<term>Etude expérimentale</term>
<term>Qualité image</term>
<term>Compression image</term>
<term>Compression donnée</term>
<term>Reconnaissance optique caractère</term>
<term>Concordance forme</term>
<term>Milieu dissipatif</term>
<term>Désadaptation</term>
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<term>Circuit sans perte</term>
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</keywords><front><div type="abstract" xml:lang="en">The JBIG2 (joint bi-level image group) standard for bi-level image coding is drafted to allow encoder designs by individuals. In JBIG2, text images are compressed by pattern matching techniques. In this paper, we propose a lossy text image compression method based on OCR (optical character recognition) which compresses bi-level images into the JBIG2 format. By processing text images with OCR, we can obtain recognition results of characters and the confidence of these results. A representative symbol image could be generated for similar character image blocks by OCR results, sizes of blocks and mismatches between blocks. This symbol image could replace all the similar image blocks and thus a high compression ratio could be achieved. Experiment results show that our algorithm achieves improvements of 75.86% over lossless SPM and 14.05% over lossy PM&S in Latin Character images, and 37.9% over lossless SPM and 4.97% over lossy PM&S in Chinese character images. Our algorithm leads to much fewer substitution errors than previous lossy PM&S and thus preserves acceptable decoded image quality.</div>
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</fA09><fA11 i1="01" i2="1"><s1>JUNQING SHANG</s1>
</fA11><fA11 i1="02" i2="1"><s1>CHANGSONG LIU</s1>
</fA11><fA11 i1="03" i2="1"><s1>XIAOQING DING</s1>
</fA11><fA12 i1="01" i2="1"><s1>TAGHVA (Kazem)</s1>
<s9>ed.</s9>
</fA12><fA12 i1="02" i2="1"><s1>LIN (Xiaofan)</s1>
<s9>ed.</s9>
</fA12><fA14 i1="01"><s1>State Key Laboratory of Intelligent Technology and Systems Department of Electronic Engineering, Tsinghua University</s1>
<s2>Beijing, 100084</s2>
<s3>CHN</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
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<s4>2006</s4>
</fA30><server><NO>PASCAL 07-0377973 INIST</NO>
<ET>JBIG2 text image compression based on OCR</ET>
<AU>JUNQING SHANG; CHANGSONG LIU; XIAOQING DING; TAGHVA (Kazem); LIN (Xiaofan)</AU>
<AF>State Key Laboratory of Intelligent Technology and Systems Department of Electronic Engineering, Tsinghua University/Beijing, 100084/Chine (1 aut., 2 aut., 3 aut.)</AF>
<DT>Publication en série; Congrès; Niveau analytique</DT>
<SO>Proceedings of SPIE, the International Society for Optical Engineering; ISSN 0277-786X; Etats-Unis; Da. 2006; Vol. 6067; 60670D.1-60670D.12; Bibl. 13 ref.</SO>
<LA>Anglais</LA>
<EA>The JBIG2 (joint bi-level image group) standard for bi-level image coding is drafted to allow encoder designs by individuals. In JBIG2, text images are compressed by pattern matching techniques. In this paper, we propose a lossy text image compression method based on OCR (optical character recognition) which compresses bi-level images into the JBIG2 format. By processing text images with OCR, we can obtain recognition results of characters and the confidence of these results. A representative symbol image could be generated for similar character image blocks by OCR results, sizes of blocks and mismatches between blocks. This symbol image could replace all the similar image blocks and thus a high compression ratio could be achieved. Experiment results show that our algorithm achieves improvements of 75.86% over lossless SPM and 14.05% over lossy PM&S in Latin Character images, and 37.9% over lossless SPM and 4.97% over lossy PM&S in Chinese character images. Our algorithm leads to much fewer substitution errors than previous lossy PM&S and thus preserves acceptable decoded image quality.</EA>
<CC>001B00G05P; 001B40B30S; 001D04A04B; 001D04A05A</CC>
<FD>Codage image; Algorithme; Etude expérimentale; Qualité image; Compression image; Compression donnée; Reconnaissance optique caractère; Concordance forme; Milieu dissipatif; Désadaptation; Taux compression; Circuit sans perte; Mesure phase; 0705P; 4230S</FD>
<ED>Image coding; Algorithms; Experimental study; Image quality; Image compression; Data compression; Optical character recognition; Pattern matching; Lossy medium; Mismatching; Compression ratio; Lossless circuit; Phase measurement</ED>
<SD>Calidad imagen; Compresión imagen; Medio dispersor; Desadaptación; Circuito sin pérdida</SD>
<LO>INIST-21760.354000153562240120</LO>
<ID>07-0377973</ID>
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