OcrV1, PascalFrancis, Curation, bibRecord, 000317

Cursive Arabic script segmentation and recognition system

Identifieur interne : 000317 ( PascalFrancis/Curation ); précédent : 000316; suivant : 000318

Cursive Arabic script segmentation and recognition system

Auteurs : T. Sari [Algérie] ; M. Sellami [Algérie]

Source :

International journal of computers & applications [ 1206-212X ] ; 2005.

RBID : Pascal:05-0282645

Descripteurs français

Pascal (Inist)
- Arabe, Segmentation, Reconnaissance caractère, Reconnaissance optique caractère, Algorithme, Mot isolé, Caractère manuscrit, Système expert, Extraction caractéristique, Evaluation performance, Réseau neuronal, Reconnaissance caractère manuscrit, Reconnaissance forme, Traitement signal, Analyse contour.

English descriptors

KwdEn :
- Algorithm, Arabic, Character recognition, Contour analysis, Expert system, Feature extraction, Handwritten character recognition, Isolated word, Manuscript character, Neural network, Optical character recognition, Pattern recognition, Performance evaluation, Segmentation, Signal processing.

Abstract

Character segmentation is a necessary preprocessing step for character recognition in many OCR systems. It is an important step because incorrectly segmented characters will not be recognized correctly. The most difficult case in character segmentation is cursive script. The scripted nature of Arabic written language poses some high challenges for automatic character segmentation and recognition. The authors present a new Character Segmentation Algorithm (ACSA) of Arabic script. The developed segmentation algorithm yields the splitting up of isolated handwritten words in perfectly separated characters. It is based on topological rules, which are constructed at the feature extraction phase. To increase ACSA's performances, it was combined it with an Arabic characters recognition system, RECAM.

A01	`01`	`1`		`@0 1206-212X`
A03		`1`		`@0 Int. j. comput. appl.`
A05				`@2 27`
A06				`@2 3`
A08	`01`	`1`	`ENG`	`@1 Cursive Arabic script segmentation and recognition system`
A11	`01`	`1`		`@1 SARI (T.)`
A11	`02`	`1`		`@1 SELLAMI (M.)`
A14	`01`			`@1 Research Laboratory in Computer Science-LRI-Annaba, Annaba University @3 DZA @Z 1 aut. @Z 2 aut.`
A20				`@1 161-168`
A21				`@1 2005`
A23	`01`			`@0 ENG`
A43	`01`			`@1 INIST @2 18064 @5 354000138066910050`
A44				`@0 0000 @1 © 2005 INIST-CNRS. All rights reserved.`
A45				`@0 25 ref.`
A47	`01`	`1`		`@0 05-0282645`
A60				`@1 P`
A61				`@0 A`
A64	`01`	`1`		`@0 International journal of computers & applications`
A66	`01`			`@0 USA`
C01	`01`		`ENG`	@0 Character segmentation is a necessary preprocessing step for character recognition in many OCR systems. It is an important step because incorrectly segmented characters will not be recognized correctly. The most difficult case in character segmentation is cursive script. The scripted nature of Arabic written language poses some high challenges for automatic character segmentation and recognition. The authors present a new Character Segmentation Algorithm (ACSA) of Arabic script. The developed segmentation algorithm yields the splitting up of isolated handwritten words in perfectly separated characters. It is based on topological rules, which are constructed at the feature extraction phase. To increase ACSA's performances, it was combined it with an Arabic characters recognition system, RECAM.
C02	`01`	`X`		`@0 001D04A05A`
C03	`01`	`X`	`FRE`	`@0 Arabe @5 01`
C03	`01`	`X`	`ENG`	`@0 Arabic @5 01`
C03	`01`	`X`	`SPA`	`@0 Árabe @5 01`
C03	`02`	`X`	`FRE`	`@0 Segmentation @5 02`
C03	`02`	`X`	`ENG`	`@0 Segmentation @5 02`
C03	`02`	`X`	`SPA`	`@0 Segmentación @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 Reconnaissance optique caractère @5 04`
C03	`04`	`X`	`ENG`	`@0 Optical character recognition @5 04`
C03	`04`	`X`	`SPA`	`@0 Reconocimento óptico de caracteres @5 04`
C03	`05`	`X`	`FRE`	`@0 Algorithme @5 05`
C03	`05`	`X`	`ENG`	`@0 Algorithm @5 05`
C03	`05`	`X`	`SPA`	`@0 Algoritmo @5 05`
C03	`06`	`X`	`FRE`	`@0 Mot isolé @5 06`
C03	`06`	`X`	`ENG`	`@0 Isolated word @5 06`
C03	`06`	`X`	`SPA`	`@0 Palabra aislada @5 06`
C03	`07`	`X`	`FRE`	`@0 Caractère manuscrit @5 07`
C03	`07`	`X`	`ENG`	`@0 Manuscript character @5 07`
C03	`07`	`X`	`SPA`	`@0 Carácter manuscrito @5 07`
C03	`08`	`X`	`FRE`	`@0 Système expert @5 08`
C03	`08`	`X`	`ENG`	`@0 Expert system @5 08`
C03	`08`	`X`	`SPA`	`@0 Sistema experto @5 08`
C03	`09`	`3`	`FRE`	`@0 Extraction caractéristique @5 09`
C03	`09`	`3`	`ENG`	`@0 Feature extraction @5 09`
C03	`10`	`X`	`FRE`	`@0 Evaluation performance @5 10`
C03	`10`	`X`	`ENG`	`@0 Performance evaluation @5 10`
C03	`10`	`X`	`SPA`	`@0 Evaluación prestación @5 10`
C03	`11`	`X`	`FRE`	`@0 Réseau neuronal @5 11`
C03	`11`	`X`	`ENG`	`@0 Neural network @5 11`
C03	`11`	`X`	`SPA`	`@0 Red neuronal @5 11`
C03	`12`	`3`	`FRE`	`@0 Reconnaissance caractère manuscrit @5 12`
C03	`12`	`3`	`ENG`	`@0 Handwritten character recognition @5 12`
C03	`13`	`X`	`FRE`	`@0 Reconnaissance forme @5 31`
C03	`13`	`X`	`ENG`	`@0 Pattern recognition @5 31`
C03	`13`	`X`	`SPA`	`@0 Reconocimiento patrón @5 31`
C03	`14`	`X`	`FRE`	`@0 Traitement signal @5 32`
C03	`14`	`X`	`ENG`	`@0 Signal processing @5 32`
C03	`14`	`X`	`SPA`	`@0 Procesamiento señal @5 32`
C03	`15`	`X`	`FRE`	`@0 Analyse contour @4 CD @5 96`
C03	`15`	`X`	`ENG`	`@0 Contour analysis @4 CD @5 96`
N21				`@1 199`

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Le document en format XML

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Cursive Arabic script segmentation and recognition system

Cursive Arabic script segmentation and recognition system

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Descripteurs français

English descriptors

Abstract

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