OcrV1, PascalFrancis, Corpus, bibRecord, 000A11

Feature extraction methods for character recognition : a survey

Identifieur interne : 000A11 ( PascalFrancis/Corpus ); précédent : 000A10; suivant : 000A12

Feature extraction methods for character recognition : a survey

Auteurs : D. Trier ; A. K. Jain ; T. Taxt

Source :

Pattern recognition [ 0031-3203 ] ; 1996.

RBID : Pascal:96-0217076

Descripteurs français

Pascal (Inist)
- Extraction forme, Reconnaissance caractère, Reconnaissance image, Invariance, Reconstructability, Character representation, OCR.

English descriptors

KwdEn :
- Character recognition, Image recognition, Invariance, OCR, Pattern extraction.

Abstract

This paper presents an overview of feature extraction methods for off-line recognition of segmented (isolated) characters. Selection of a feature extraction method is probably the single most important factor in achieving high recognition performance in character recognition systems. Different feature extraction methods are designed for different representations of the characters, such as solid binary characters, character contours, skeletons (thinned characters) or gray-level subimages of each individual character. The feature extraction methods are discussed in terms of invariance properties, reconstructability and expected distortions and variability of the characters. The problem of choosing the appropriate feature extraction method for a given application is also discussed. When a few promising feature extraction methods have been identified, they need to be evaluated experimentally to find the best method for the given application.

Notice en format standard (ISO 2709)

Pour connaître la documentation sur le format Inist Standard.

A01	`01`	`1`		`@0 0031-3203`
A02	`01`			`@0 PTNRA8`
A03		`1`		`@0 Pattern recogn.`
A05				`@2 29`
A06				`@2 4`
A08	`01`	`1`	`ENG`	`@1 Feature extraction methods for character recognition : a survey`
A11	`01`	`1`		`@1 TRIER (Ø. D.)`
A11	`02`	`1`		`@1 JAIN (A. K.)`
A11	`03`	`1`		`@1 TAXT (T.)`
A14	`01`			`@1 Department of Informatics, University of Oslo, P.O. Box 1080 Blindern @2 0316 Oslo @3 NOR @Z 1 aut. @Z 3 aut.`
A20				`@1 641-662`
A21				`@1 1996`
A23	`01`			`@0 ENG`
A43	`01`			`@1 INIST @2 15220 @5 354000055441360100`
A44				`@0 0000`
A45				`@0 92 ref.`
A47	`01`	`1`		`@0 96-0217076`
A60				`@1 P`
A61				`@0 A`
A64	`01`	`1`		`@0 Pattern recognition`
A66	`01`			`@0 GBR`
C01	`01`		`ENG`	@0 This paper presents an overview of feature extraction methods for off-line recognition of segmented (isolated) characters. Selection of a feature extraction method is probably the single most important factor in achieving high recognition performance in character recognition systems. Different feature extraction methods are designed for different representations of the characters, such as solid binary characters, character contours, skeletons (thinned characters) or gray-level subimages of each individual character. The feature extraction methods are discussed in terms of invariance properties, reconstructability and expected distortions and variability of the characters. The problem of choosing the appropriate feature extraction method for a given application is also discussed. When a few promising feature extraction methods have been identified, they need to be evaluated experimentally to find the best method for the given application.
C02	`01`	`X`		`@0 001D02C03`
C03	`01`	`X`	`FRE`	`@0 Extraction forme @5 01`
C03	`01`	`X`	`ENG`	`@0 Pattern extraction @5 01`
C03	`01`	`X`	`SPA`	`@0 Extracción forma @5 01`
C03	`02`	`X`	`FRE`	`@0 Reconnaissance caractère @5 02`
C03	`02`	`X`	`ENG`	`@0 Character recognition @5 02`
C03	`02`	`X`	`SPA`	`@0 Reconocimiento carácter @5 02`
C03	`03`	`X`	`FRE`	`@0 Reconnaissance image @5 03`
C03	`03`	`X`	`ENG`	`@0 Image recognition @5 03`
C03	`03`	`X`	`SPA`	`@0 Reconocimiento imagen @5 03`
C03	`04`	`X`	`FRE`	`@0 Invariance @5 04`
C03	`04`	`X`	`ENG`	`@0 Invariance @5 04`
C03	`04`	`X`	`SPA`	`@0 Invarianza @5 04`
C03	`05`	`X`	`FRE`	`@0 Reconstructability @4 INC @5 72`
C03	`06`	`X`	`FRE`	`@0 Character representation @4 INC @5 73`
C03	`07`	`X`	`FRE`	`@0 OCR @4 CD @5 96`
C03	`07`	`X`	`ENG`	`@0 OCR @4 CD @5 96`
N21				`@1 148`

Format Inist (serveur)

NO :	PASCAL 96-0217076 INIST
ET :	Feature extraction methods for character recognition : a survey
AU :	TRIER (Ø. D.); JAIN (A. K.); TAXT (T.)
AF :	Department of Informatics, University of Oslo, P.O. Box 1080 Blindern/0316 Oslo/Norvège (1 aut., 3 aut.)
DT :	Publication en série; Niveau analytique
SO :	Pattern recognition; ISSN 0031-3203; Coden PTNRA8; Royaume-Uni; Da. 1996; Vol. 29; No. 4; Pp. 641-662; Bibl. 92 ref.
LA :	Anglais
EA :	This paper presents an overview of feature extraction methods for off-line recognition of segmented (isolated) characters. Selection of a feature extraction method is probably the single most important factor in achieving high recognition performance in character recognition systems. Different feature extraction methods are designed for different representations of the characters, such as solid binary characters, character contours, skeletons (thinned characters) or gray-level subimages of each individual character. The feature extraction methods are discussed in terms of invariance properties, reconstructability and expected distortions and variability of the characters. The problem of choosing the appropriate feature extraction method for a given application is also discussed. When a few promising feature extraction methods have been identified, they need to be evaluated experimentally to find the best method for the given application.
CC :	001D02C03
FD :	Extraction forme; Reconnaissance caractère; Reconnaissance image; Invariance; Reconstructability; Character representation; OCR
ED :	Pattern extraction; Character recognition; Image recognition; Invariance; OCR
SD :	Extracción forma; Reconocimiento carácter; Reconocimiento imagen; Invarianza
LO :	INIST-15220.354000055441360100
ID :	96-0217076

Links to Exploration step

Pascal:96-0217076

Le document en format XML

<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en" level="a">Feature extraction methods for character recognition : a survey</title>
<author><name sortKey="Trier,  D" sort="Trier,  D" uniqKey="Trier  " first=" D." last="Trier"> D. Trier</name>
<affiliation><inist:fA14 i1="01"><s1>Department of Informatics, University of Oslo, P.O. Box 1080 Blindern</s1>
<s2>0316 Oslo</s2>
<s3>NOR</s3>
<sZ>1 aut.</sZ>
<sZ>3 aut.</sZ>
</inist:fA14>
</affiliation>
</author>
<author><name sortKey="Jain, A K" sort="Jain, A K" uniqKey="Jain A" first="A. K." last="Jain">A. K. Jain</name>
</author>
<author><name sortKey="Taxt, T" sort="Taxt, T" uniqKey="Taxt T" first="T." last="Taxt">T. Taxt</name>
<affiliation><inist:fA14 i1="01"><s1>Department of Informatics, University of Oslo, P.O. Box 1080 Blindern</s1>
<s2>0316 Oslo</s2>
<s3>NOR</s3>
<sZ>1 aut.</sZ>
<sZ>3 aut.</sZ>
</inist:fA14>
</affiliation>
</author>
</titleStmt>
<publicationStmt><idno type="wicri:source">INIST</idno>
<idno type="inist">96-0217076</idno>
<date when="1996">1996</date>
<idno type="stanalyst">PASCAL 96-0217076 INIST</idno>
<idno type="RBID">Pascal:96-0217076</idno>
<idno type="wicri:Area/PascalFrancis/Corpus">000A11</idno>
</publicationStmt>
<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a">Feature extraction methods for character recognition : a survey</title>
<author><name sortKey="Trier,  D" sort="Trier,  D" uniqKey="Trier  " first=" D." last="Trier"> D. Trier</name>
<affiliation><inist:fA14 i1="01"><s1>Department of Informatics, University of Oslo, P.O. Box 1080 Blindern</s1>
<s2>0316 Oslo</s2>
<s3>NOR</s3>
<sZ>1 aut.</sZ>
<sZ>3 aut.</sZ>
</inist:fA14>
</affiliation>
</author>
<author><name sortKey="Jain, A K" sort="Jain, A K" uniqKey="Jain A" first="A. K." last="Jain">A. K. Jain</name>
</author>
<author><name sortKey="Taxt, T" sort="Taxt, T" uniqKey="Taxt T" first="T." last="Taxt">T. Taxt</name>
<affiliation><inist:fA14 i1="01"><s1>Department of Informatics, University of Oslo, P.O. Box 1080 Blindern</s1>
<s2>0316 Oslo</s2>
<s3>NOR</s3>
<sZ>1 aut.</sZ>
<sZ>3 aut.</sZ>
</inist:fA14>
</affiliation>
</author>
</analytic>
<series><title level="j" type="main">Pattern recognition</title>
<title level="j" type="abbreviated">Pattern recogn.</title>
<idno type="ISSN">0031-3203</idno>
<imprint><date when="1996">1996</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
<seriesStmt><title level="j" type="main">Pattern recognition</title>
<title level="j" type="abbreviated">Pattern recogn.</title>
<idno type="ISSN">0031-3203</idno>
</seriesStmt>
</fileDesc>
<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Character recognition</term>
<term>Image recognition</term>
<term>Invariance</term>
<term>OCR</term>
<term>Pattern extraction</term>
</keywords>
<keywords scheme="Pascal" xml:lang="fr"><term>Extraction forme</term>
<term>Reconnaissance caractère</term>
<term>Reconnaissance image</term>
<term>Invariance</term>
<term>Reconstructability</term>
<term>Character representation</term>
<term>OCR</term>
</keywords>
</textClass>
</profileDesc>
</teiHeader>
<front><div type="abstract" xml:lang="en">This paper presents an overview of feature extraction methods for off-line recognition of segmented (isolated) characters. Selection of a feature extraction method is probably the single most important factor in achieving high recognition performance in character recognition systems. Different feature extraction methods are designed for different representations of the characters, such as solid binary characters, character contours, skeletons (thinned characters) or gray-level subimages of each individual character. The feature extraction methods are discussed in terms of invariance properties, reconstructability and expected distortions and variability of the characters. The problem of choosing the appropriate feature extraction method for a given application is also discussed. When a few promising feature extraction methods have been identified, they need to be evaluated experimentally to find the best method for the given application.</div>
</front>
</TEI>
<inist><standard h6="B"><pA><fA01 i1="01" i2="1"><s0>0031-3203</s0>
</fA01>
<fA02 i1="01"><s0>PTNRA8</s0>
</fA02>
<fA03 i2="1"><s0>Pattern recogn.</s0>
</fA03>
<fA05><s2>29</s2>
</fA05>
<fA06><s2>4</s2>
</fA06>
<fA08 i1="01" i2="1" l="ENG"><s1>Feature extraction methods for character recognition : a survey</s1>
</fA08>
<fA11 i1="01" i2="1"><s1>TRIER (Ø. D.)</s1>
</fA11>
<fA11 i1="02" i2="1"><s1>JAIN (A. K.)</s1>
</fA11>
<fA11 i1="03" i2="1"><s1>TAXT (T.)</s1>
</fA11>
<fA14 i1="01"><s1>Department of Informatics, University of Oslo, P.O. Box 1080 Blindern</s1>
<s2>0316 Oslo</s2>
<s3>NOR</s3>
<sZ>1 aut.</sZ>
<sZ>3 aut.</sZ>
</fA14>
<fA20><s1>641-662</s1>
</fA20>
<fA21><s1>1996</s1>
</fA21>
<fA23 i1="01"><s0>ENG</s0>
</fA23>
<fA43 i1="01"><s1>INIST</s1>
<s2>15220</s2>
<s5>354000055441360100</s5>
</fA43>
<fA44><s0>0000</s0>
</fA44>
<fA45><s0>92 ref.</s0>
</fA45>
<fA47 i1="01" i2="1"><s0>96-0217076</s0>
</fA47>
<fA60><s1>P</s1>
</fA60>
<fA61><s0>A</s0>
</fA61>
<fA64 i1="01" i2="1"><s0>Pattern recognition</s0>
</fA64>
<fA66 i1="01"><s0>GBR</s0>
</fA66>
<fC01 i1="01" l="ENG"><s0>This paper presents an overview of feature extraction methods for off-line recognition of segmented (isolated) characters. Selection of a feature extraction method is probably the single most important factor in achieving high recognition performance in character recognition systems. Different feature extraction methods are designed for different representations of the characters, such as solid binary characters, character contours, skeletons (thinned characters) or gray-level subimages of each individual character. The feature extraction methods are discussed in terms of invariance properties, reconstructability and expected distortions and variability of the characters. The problem of choosing the appropriate feature extraction method for a given application is also discussed. When a few promising feature extraction methods have been identified, they need to be evaluated experimentally to find the best method for the given application.</s0>
</fC01>
<fC02 i1="01" i2="X"><s0>001D02C03</s0>
</fC02>
<fC03 i1="01" i2="X" l="FRE"><s0>Extraction forme</s0>
<s5>01</s5>
</fC03>
<fC03 i1="01" i2="X" l="ENG"><s0>Pattern extraction</s0>
<s5>01</s5>
</fC03>
<fC03 i1="01" i2="X" l="SPA"><s0>Extracción forma</s0>
<s5>01</s5>
</fC03>
<fC03 i1="02" i2="X" l="FRE"><s0>Reconnaissance caractère</s0>
<s5>02</s5>
</fC03>
<fC03 i1="02" i2="X" l="ENG"><s0>Character recognition</s0>
<s5>02</s5>
</fC03>
<fC03 i1="02" i2="X" l="SPA"><s0>Reconocimiento carácter</s0>
<s5>02</s5>
</fC03>
<fC03 i1="03" i2="X" l="FRE"><s0>Reconnaissance image</s0>
<s5>03</s5>
</fC03>
<fC03 i1="03" i2="X" l="ENG"><s0>Image recognition</s0>
<s5>03</s5>
</fC03>
<fC03 i1="03" i2="X" l="SPA"><s0>Reconocimiento imagen</s0>
<s5>03</s5>
</fC03>
<fC03 i1="04" i2="X" l="FRE"><s0>Invariance</s0>
<s5>04</s5>
</fC03>
<fC03 i1="04" i2="X" l="ENG"><s0>Invariance</s0>
<s5>04</s5>
</fC03>
<fC03 i1="04" i2="X" l="SPA"><s0>Invarianza</s0>
<s5>04</s5>
</fC03>
<fC03 i1="05" i2="X" l="FRE"><s0>Reconstructability</s0>
<s4>INC</s4>
<s5>72</s5>
</fC03>
<fC03 i1="06" i2="X" l="FRE"><s0>Character representation</s0>
<s4>INC</s4>
<s5>73</s5>
</fC03>
<fC03 i1="07" i2="X" l="FRE"><s0>OCR</s0>
<s4>CD</s4>
<s5>96</s5>
</fC03>
<fC03 i1="07" i2="X" l="ENG"><s0>OCR</s0>
<s4>CD</s4>
<s5>96</s5>
</fC03>
<fN21><s1>148</s1>
</fN21>
</pA>
</standard>
<server><NO>PASCAL 96-0217076 INIST</NO>
<ET>Feature extraction methods for character recognition : a survey</ET>
<AU>TRIER (Ø. D.); JAIN (A. K.); TAXT (T.)</AU>
<AF>Department of Informatics, University of Oslo, P.O. Box 1080 Blindern/0316 Oslo/Norvège (1 aut., 3 aut.)</AF>
<DT>Publication en série; Niveau analytique</DT>
<SO>Pattern recognition; ISSN 0031-3203; Coden PTNRA8; Royaume-Uni; Da. 1996; Vol. 29; No. 4; Pp. 641-662; Bibl. 92 ref.</SO>
<LA>Anglais</LA>
<EA>This paper presents an overview of feature extraction methods for off-line recognition of segmented (isolated) characters. Selection of a feature extraction method is probably the single most important factor in achieving high recognition performance in character recognition systems. Different feature extraction methods are designed for different representations of the characters, such as solid binary characters, character contours, skeletons (thinned characters) or gray-level subimages of each individual character. The feature extraction methods are discussed in terms of invariance properties, reconstructability and expected distortions and variability of the characters. The problem of choosing the appropriate feature extraction method for a given application is also discussed. When a few promising feature extraction methods have been identified, they need to be evaluated experimentally to find the best method for the given application.</EA>
<CC>001D02C03</CC>
<FD>Extraction forme; Reconnaissance caractère; Reconnaissance image; Invariance; Reconstructability; Character representation; OCR</FD>
<ED>Pattern extraction; Character recognition; Image recognition; Invariance; OCR</ED>
<SD>Extracción forma; Reconocimiento carácter; Reconocimiento imagen; Invarianza</SD>
<LO>INIST-15220.354000055441360100</LO>
<ID>96-0217076</ID>
</server>
</inist>
</record>

Pour manipuler ce document sous Unix (Dilib)

EXPLOR_STEP=$WICRI_ROOT/Ticri/CIDE/explor/OcrV1/Data/PascalFrancis/Corpus

HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000A11 | SxmlIndent | more

HfdSelect -h $EXPLOR_AREA/Data/PascalFrancis/Corpus/biblio.hfd -nk 000A11 | SxmlIndent | more

Pour mettre un lien sur cette page dans le réseau Wicri

{{Explor lien
   |wiki=    Ticri/CIDE
   |area=    OcrV1
   |flux=    PascalFrancis
   |étape=   Corpus
   |type=    RBID
   |clé=     Pascal:96-0217076
   |texte=   Feature extraction methods for character recognition : a survey
}}

This area was generated with Dilib version V0.6.32.
Data generation: Sat Nov 11 16:53:45 2017. Site generation: Mon Mar 11 23:15:16 2024

	Serveur d'exploration sur l'OCR
	Attention, ce site est en cours de développement ! Attention, site généré par des moyens informatiques à partir de corpus bruts. Les informations ne sont donc pas validées.

Serveur d'exploration sur l'OCR

Feature extraction methods for character recognition : a survey

Feature extraction methods for character recognition : a survey

Source :

Descripteurs français

English descriptors

Abstract

Notice en format standard (ISO 2709)

Format Inist (serveur)

Links to Exploration step

Le document en format XML

Pour manipuler ce document sous Unix (Dilib)

Pour mettre un lien sur cette page dans le réseau Wicri