OcrV1, PascalFrancis, Corpus, bibRecord, 000061

An approach to offline handwritten Devanagari word segmentation

Identifieur interne : 000061 ( PascalFrancis/Corpus ); précédent : 000060; suivant : 000062

An approach to offline handwritten Devanagari word segmentation

Auteurs : O. V. Ramana Murthy ; M. Hanmandlu

Source :

International journal of computer applications in technology [ 0952-8091 ] ; 2012.

RBID : Pascal:13-0071293

Descripteurs français

Pascal (Inist)
- Caractère manuscrit, Linguistique, Langage naturel, Reconnaissance caractère, Reconnaissance optique caractère, Typographie, Segmentation, Transformation Hough.

English descriptors

KwdEn :
- Character recognition, Hough transformation, Linguistics, Manuscript character, Natural language, Optical character recognition, Segmentation, Typography.

Abstract

Hindi is very popular language after Mandarin and English. Its script is Devanagari. Although major work is reported on OCR techniques for machine printed Devanagari script, very few works are beginning to report on offline handwritten Devanagari OCR. Particularly, very few works have been reported so far, on segmentation of Devanagari words. This paper paves a step in that direction and open avenues for researchers in that field. A novel segmentation approach is proposed for segmentation of offline handwritten Devanagari words using techniques of Hough transform and connected components. The difficulties for segmentation in Devanagari script and systematic steps to accommodate those difficulties as much as possible have been presented with elaborate results.

Notice en format standard (ISO 2709)

Pour connaître la documentation sur le format Inist Standard.

A01	`01`	`1`		`@0 0952-8091`
A03		`1`		`@0 Int. j. comput. appl. technol.`
A05				`@2 44`
A06				`@2 4`
A08	`01`	`1`	`ENG`	`@1 An approach to offline handwritten Devanagari word segmentation`
A11	`01`	`1`		`@1 RAMANA MURTHY (O. V.)`
A11	`02`	`1`		`@1 HANMANDLU (M.)`
A14	`01`			`@1 Department of Electrical Engineering @2 IIT Delhi @3 IND @Z 1 aut. @Z 2 aut.`
A20				`@1 284-292`
A21				`@1 2012`
A23	`01`			`@0 ENG`
A43	`01`			`@1 INIST @2 27542 @5 354000505462420060`
A44				`@0 0000 @1 © 2013 INIST-CNRS. All rights reserved.`
A45				`@0 1/4 p.`
A47	`01`	`1`		`@0 13-0071293`
A60				`@1 P`
A61				`@0 A`
A64	`01`	`1`		`@0 International journal of computer applications in technology`
A66	`01`			`@0 CHE`
C01	`01`		`ENG`	@0 Hindi is very popular language after Mandarin and English. Its script is Devanagari. Although major work is reported on OCR techniques for machine printed Devanagari script, very few works are beginning to report on offline handwritten Devanagari OCR. Particularly, very few works have been reported so far, on segmentation of Devanagari words. This paper paves a step in that direction and open avenues for researchers in that field. A novel segmentation approach is proposed for segmentation of offline handwritten Devanagari words using techniques of Hough transform and connected components. The difficulties for segmentation in Devanagari script and systematic steps to accommodate those difficulties as much as possible have been presented with elaborate results.
C02	`01`	`X`		`@0 001D02C04`
C02	`02`	`X`		`@0 001D02C03`
C03	`01`	`X`	`FRE`	`@0 Caractère manuscrit @5 06`
C03	`01`	`X`	`ENG`	`@0 Manuscript character @5 06`
C03	`01`	`X`	`SPA`	`@0 Carácter manuscrito @5 06`
C03	`02`	`X`	`FRE`	`@0 Linguistique @5 07`
C03	`02`	`X`	`ENG`	`@0 Linguistics @5 07`
C03	`02`	`X`	`SPA`	`@0 Linguística @5 07`
C03	`03`	`X`	`FRE`	`@0 Langage naturel @5 08`
C03	`03`	`X`	`ENG`	`@0 Natural language @5 08`
C03	`03`	`X`	`SPA`	`@0 Lenguaje natural @5 08`
C03	`04`	`X`	`FRE`	`@0 Reconnaissance caractère @5 09`
C03	`04`	`X`	`ENG`	`@0 Character recognition @5 09`
C03	`04`	`X`	`SPA`	`@0 Reconocimiento carácter @5 09`
C03	`05`	`X`	`FRE`	`@0 Reconnaissance optique caractère @5 10`
C03	`05`	`X`	`ENG`	`@0 Optical character recognition @5 10`
C03	`05`	`X`	`SPA`	`@0 Reconocimento óptico de caracteres @5 10`
C03	`06`	`X`	`FRE`	`@0 Typographie @5 18`
C03	`06`	`X`	`ENG`	`@0 Typography @5 18`
C03	`06`	`X`	`SPA`	`@0 Tipografía @5 18`
C03	`07`	`X`	`FRE`	`@0 Segmentation @5 23`
C03	`07`	`X`	`ENG`	`@0 Segmentation @5 23`
C03	`07`	`X`	`SPA`	`@0 Segmentación @5 23`
C03	`08`	`X`	`FRE`	`@0 Transformation Hough @5 24`
C03	`08`	`X`	`ENG`	`@0 Hough transformation @5 24`
C03	`08`	`X`	`SPA`	`@0 Transformación Hough @5 24`
N21				`@1 042`
N44	`01`			`@1 OTO`
N82				`@1 OTO`

Format Inist (serveur)

NO :	PASCAL 13-0071293 INIST
ET :	An approach to offline handwritten Devanagari word segmentation
AU :	RAMANA MURTHY (O. V.); HANMANDLU (M.)
AF :	Department of Electrical Engineering/IIT Delhi/Inde (1 aut., 2 aut.)
DT :	Publication en série; Niveau analytique
SO :	International journal of computer applications in technology; ISSN 0952-8091; Suisse; Da. 2012; Vol. 44; No. 4; Pp. 284-292; Bibl. 1/4 p.
LA :	Anglais
EA :	Hindi is very popular language after Mandarin and English. Its script is Devanagari. Although major work is reported on OCR techniques for machine printed Devanagari script, very few works are beginning to report on offline handwritten Devanagari OCR. Particularly, very few works have been reported so far, on segmentation of Devanagari words. This paper paves a step in that direction and open avenues for researchers in that field. A novel segmentation approach is proposed for segmentation of offline handwritten Devanagari words using techniques of Hough transform and connected components. The difficulties for segmentation in Devanagari script and systematic steps to accommodate those difficulties as much as possible have been presented with elaborate results.
CC :	001D02C04; 001D02C03
FD :	Caractère manuscrit; Linguistique; Langage naturel; Reconnaissance caractère; Reconnaissance optique caractère; Typographie; Segmentation; Transformation Hough
ED :	Manuscript character; Linguistics; Natural language; Character recognition; Optical character recognition; Typography; Segmentation; Hough transformation
SD :	Carácter manuscrito; Linguística; Lenguaje natural; Reconocimiento carácter; Reconocimento óptico de caracteres; Tipografía; Segmentación; Transformación Hough
LO :	INIST-27542.354000505462420060
ID :	13-0071293

Links to Exploration step

Pascal:13-0071293

Le document en format XML

<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en" level="a">An approach to offline handwritten Devanagari word segmentation</title>
<author><name sortKey="Ramana Murthy, O V" sort="Ramana Murthy, O V" uniqKey="Ramana Murthy O" first="O. V." last="Ramana Murthy">O. V. Ramana Murthy</name>
<affiliation><inist:fA14 i1="01"><s1>Department of Electrical Engineering</s1>
<s2>IIT Delhi</s2>
<s3>IND</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
</inist:fA14>
</affiliation>
</author>
<author><name sortKey="Hanmandlu, M" sort="Hanmandlu, M" uniqKey="Hanmandlu M" first="M." last="Hanmandlu">M. Hanmandlu</name>
<affiliation><inist:fA14 i1="01"><s1>Department of Electrical Engineering</s1>
<s2>IIT Delhi</s2>
<s3>IND</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
</inist:fA14>
</affiliation>
</author>
</titleStmt>
<publicationStmt><idno type="wicri:source">INIST</idno>
<idno type="inist">13-0071293</idno>
<date when="2012">2012</date>
<idno type="stanalyst">PASCAL 13-0071293 INIST</idno>
<idno type="RBID">Pascal:13-0071293</idno>
<idno type="wicri:Area/PascalFrancis/Corpus">000061</idno>
</publicationStmt>
<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a">An approach to offline handwritten Devanagari word segmentation</title>
<author><name sortKey="Ramana Murthy, O V" sort="Ramana Murthy, O V" uniqKey="Ramana Murthy O" first="O. V." last="Ramana Murthy">O. V. Ramana Murthy</name>
<affiliation><inist:fA14 i1="01"><s1>Department of Electrical Engineering</s1>
<s2>IIT Delhi</s2>
<s3>IND</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
</inist:fA14>
</affiliation>
</author>
<author><name sortKey="Hanmandlu, M" sort="Hanmandlu, M" uniqKey="Hanmandlu M" first="M." last="Hanmandlu">M. Hanmandlu</name>
<affiliation><inist:fA14 i1="01"><s1>Department of Electrical Engineering</s1>
<s2>IIT Delhi</s2>
<s3>IND</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
</inist:fA14>
</affiliation>
</author>
</analytic>
<series><title level="j" type="main">International journal of computer applications in technology</title>
<title level="j" type="abbreviated">Int. j. comput. appl. technol.</title>
<idno type="ISSN">0952-8091</idno>
<imprint><date when="2012">2012</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
<seriesStmt><title level="j" type="main">International journal of computer applications in technology</title>
<title level="j" type="abbreviated">Int. j. comput. appl. technol.</title>
<idno type="ISSN">0952-8091</idno>
</seriesStmt>
</fileDesc>
<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Character recognition</term>
<term>Hough transformation</term>
<term>Linguistics</term>
<term>Manuscript character</term>
<term>Natural language</term>
<term>Optical character recognition</term>
<term>Segmentation</term>
<term>Typography</term>
</keywords>
<keywords scheme="Pascal" xml:lang="fr"><term>Caractère manuscrit</term>
<term>Linguistique</term>
<term>Langage naturel</term>
<term>Reconnaissance caractère</term>
<term>Reconnaissance optique caractère</term>
<term>Typographie</term>
<term>Segmentation</term>
<term>Transformation Hough</term>
</keywords>
</textClass>
</profileDesc>
</teiHeader>
<front><div type="abstract" xml:lang="en">Hindi is very popular language after Mandarin and English. Its script is Devanagari. Although major work is reported on OCR techniques for machine printed Devanagari script, very few works are beginning to report on offline handwritten Devanagari OCR. Particularly, very few works have been reported so far, on segmentation of Devanagari words. This paper paves a step in that direction and open avenues for researchers in that field. A novel segmentation approach is proposed for segmentation of offline handwritten Devanagari words using techniques of Hough transform and connected components. The difficulties for segmentation in Devanagari script and systematic steps to accommodate those difficulties as much as possible have been presented with elaborate results.</div>
</front>
</TEI>
<inist><standard h6="B"><pA><fA01 i1="01" i2="1"><s0>0952-8091</s0>
</fA01>
<fA03 i2="1"><s0>Int. j. comput. appl. technol.</s0>
</fA03>
<fA05><s2>44</s2>
</fA05>
<fA06><s2>4</s2>
</fA06>
<fA08 i1="01" i2="1" l="ENG"><s1>An approach to offline handwritten Devanagari word segmentation</s1>
</fA08>
<fA11 i1="01" i2="1"><s1>RAMANA MURTHY (O. V.)</s1>
</fA11>
<fA11 i1="02" i2="1"><s1>HANMANDLU (M.)</s1>
</fA11>
<fA14 i1="01"><s1>Department of Electrical Engineering</s1>
<s2>IIT Delhi</s2>
<s3>IND</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
</fA14>
<fA20><s1>284-292</s1>
</fA20>
<fA21><s1>2012</s1>
</fA21>
<fA23 i1="01"><s0>ENG</s0>
</fA23>
<fA43 i1="01"><s1>INIST</s1>
<s2>27542</s2>
<s5>354000505462420060</s5>
</fA43>
<fA44><s0>0000</s0>
<s1>© 2013 INIST-CNRS. All rights reserved.</s1>
</fA44>
<fA45><s0>1/4 p.</s0>
</fA45>
<fA47 i1="01" i2="1"><s0>13-0071293</s0>
</fA47>
<fA60><s1>P</s1>
</fA60>
<fA61><s0>A</s0>
</fA61>
<fA64 i1="01" i2="1"><s0>International journal of computer applications in technology</s0>
</fA64>
<fA66 i1="01"><s0>CHE</s0>
</fA66>
<fC01 i1="01" l="ENG"><s0>Hindi is very popular language after Mandarin and English. Its script is Devanagari. Although major work is reported on OCR techniques for machine printed Devanagari script, very few works are beginning to report on offline handwritten Devanagari OCR. Particularly, very few works have been reported so far, on segmentation of Devanagari words. This paper paves a step in that direction and open avenues for researchers in that field. A novel segmentation approach is proposed for segmentation of offline handwritten Devanagari words using techniques of Hough transform and connected components. The difficulties for segmentation in Devanagari script and systematic steps to accommodate those difficulties as much as possible have been presented with elaborate results.</s0>
</fC01>
<fC02 i1="01" i2="X"><s0>001D02C04</s0>
</fC02>
<fC02 i1="02" i2="X"><s0>001D02C03</s0>
</fC02>
<fC03 i1="01" i2="X" l="FRE"><s0>Caractère manuscrit</s0>
<s5>06</s5>
</fC03>
<fC03 i1="01" i2="X" l="ENG"><s0>Manuscript character</s0>
<s5>06</s5>
</fC03>
<fC03 i1="01" i2="X" l="SPA"><s0>Carácter manuscrito</s0>
<s5>06</s5>
</fC03>
<fC03 i1="02" i2="X" l="FRE"><s0>Linguistique</s0>
<s5>07</s5>
</fC03>
<fC03 i1="02" i2="X" l="ENG"><s0>Linguistics</s0>
<s5>07</s5>
</fC03>
<fC03 i1="02" i2="X" l="SPA"><s0>Linguística</s0>
<s5>07</s5>
</fC03>
<fC03 i1="03" i2="X" l="FRE"><s0>Langage naturel</s0>
<s5>08</s5>
</fC03>
<fC03 i1="03" i2="X" l="ENG"><s0>Natural language</s0>
<s5>08</s5>
</fC03>
<fC03 i1="03" i2="X" l="SPA"><s0>Lenguaje natural</s0>
<s5>08</s5>
</fC03>
<fC03 i1="04" i2="X" l="FRE"><s0>Reconnaissance caractère</s0>
<s5>09</s5>
</fC03>
<fC03 i1="04" i2="X" l="ENG"><s0>Character recognition</s0>
<s5>09</s5>
</fC03>
<fC03 i1="04" i2="X" l="SPA"><s0>Reconocimiento carácter</s0>
<s5>09</s5>
</fC03>
<fC03 i1="05" i2="X" l="FRE"><s0>Reconnaissance optique caractère</s0>
<s5>10</s5>
</fC03>
<fC03 i1="05" i2="X" l="ENG"><s0>Optical character recognition</s0>
<s5>10</s5>
</fC03>
<fC03 i1="05" i2="X" l="SPA"><s0>Reconocimento óptico de caracteres</s0>
<s5>10</s5>
</fC03>
<fC03 i1="06" i2="X" l="FRE"><s0>Typographie</s0>
<s5>18</s5>
</fC03>
<fC03 i1="06" i2="X" l="ENG"><s0>Typography</s0>
<s5>18</s5>
</fC03>
<fC03 i1="06" i2="X" l="SPA"><s0>Tipografía</s0>
<s5>18</s5>
</fC03>
<fC03 i1="07" i2="X" l="FRE"><s0>Segmentation</s0>
<s5>23</s5>
</fC03>
<fC03 i1="07" i2="X" l="ENG"><s0>Segmentation</s0>
<s5>23</s5>
</fC03>
<fC03 i1="07" i2="X" l="SPA"><s0>Segmentación</s0>
<s5>23</s5>
</fC03>
<fC03 i1="08" i2="X" l="FRE"><s0>Transformation Hough</s0>
<s5>24</s5>
</fC03>
<fC03 i1="08" i2="X" l="ENG"><s0>Hough transformation</s0>
<s5>24</s5>
</fC03>
<fC03 i1="08" i2="X" l="SPA"><s0>Transformación Hough</s0>
<s5>24</s5>
</fC03>
<fN21><s1>042</s1>
</fN21>
<fN44 i1="01"><s1>OTO</s1>
</fN44>
<fN82><s1>OTO</s1>
</fN82>
</pA>
</standard>
<server><NO>PASCAL 13-0071293 INIST</NO>
<ET>An approach to offline handwritten Devanagari word segmentation</ET>
<AU>RAMANA MURTHY (O. V.); HANMANDLU (M.)</AU>
<AF>Department of Electrical Engineering/IIT Delhi/Inde (1 aut., 2 aut.)</AF>
<DT>Publication en série; Niveau analytique</DT>
<SO>International journal of computer applications in technology; ISSN 0952-8091; Suisse; Da. 2012; Vol. 44; No. 4; Pp. 284-292; Bibl. 1/4 p.</SO>
<LA>Anglais</LA>
<EA>Hindi is very popular language after Mandarin and English. Its script is Devanagari. Although major work is reported on OCR techniques for machine printed Devanagari script, very few works are beginning to report on offline handwritten Devanagari OCR. Particularly, very few works have been reported so far, on segmentation of Devanagari words. This paper paves a step in that direction and open avenues for researchers in that field. A novel segmentation approach is proposed for segmentation of offline handwritten Devanagari words using techniques of Hough transform and connected components. The difficulties for segmentation in Devanagari script and systematic steps to accommodate those difficulties as much as possible have been presented with elaborate results.</EA>
<CC>001D02C04; 001D02C03</CC>
<FD>Caractère manuscrit; Linguistique; Langage naturel; Reconnaissance caractère; Reconnaissance optique caractère; Typographie; Segmentation; Transformation Hough</FD>
<ED>Manuscript character; Linguistics; Natural language; Character recognition; Optical character recognition; Typography; Segmentation; Hough transformation</ED>
<SD>Carácter manuscrito; Linguística; Lenguaje natural; Reconocimiento carácter; Reconocimento óptico de caracteres; Tipografía; Segmentación; Transformación Hough</SD>
<LO>INIST-27542.354000505462420060</LO>
<ID>13-0071293</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 000061 | SxmlIndent | more

HfdSelect -h $EXPLOR_AREA/Data/PascalFrancis/Corpus/biblio.hfd -nk 000061 | 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:13-0071293
   |texte=   An approach to offline handwritten Devanagari word segmentation
}}

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

An approach to offline handwritten Devanagari word segmentation

An approach to offline handwritten Devanagari word segmentation

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