Recognition of handwritten Tifinagh characters using a multilayer neural networks and hidden Markov model

C. DAOUI

Recognition of handwritten Tifinagh characters using a multilayer neural networks and hidden Markov model

bade10 * §

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C. DAOUI

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kamalmoro

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bbouikhalene

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Youness Lakhdoura

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§ University Sultan Moulay Slimane

Recognition of handwritten Tifinagh characters using a multilayer neural networks and hidden Markov model

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Abstract

In this paper, we propose a system for recognition handwritten characters Tifinagh, with the use of neural networks (the multi layer perceptron MLP), the hidden Markov model (HMM), the hybrid Model MLP/HMM and a feature extraction method based on mathematical morphology, this method is tested on the database of handwritten isolated characters Tifinagh size consistent (1800 images in learning and 5400 test examples). The recognition rate found is 92.33%. The MLP, HMM and MLP+HMM classifiers show good enough results.

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

bade10, C. DAOUI, kamalmoro, bbouikhalene, Youness Lakhdoura. 1970. "Recognition of handwritten Tifinagh characters using a multilayer neural networks and hidden Markov model". Global Journal of Computer Science and Technology GJCST Volume 11 (GJCST Volume 11 Issue 15).

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GJCST Volume 11 Issue 15

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

Hidden Markov Model Hybrid Model mathematical morphology Neural Network Recognition of handwritten characters Tifinagh characters

Classification

GJCST Classification G.3

F.1.1

Submission ReceivedJuly 10, 2011
Peer Review Double Blind
Handling Editor
Accepted August 8, 2011
Published August 22, 2011

Version of record

v1.2

Issue date

September 7, 2011

Language

English

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Article Matrices

Total Score: 170

Country: Morocco

Subject: Global Journal of Computer Science and Technology

Authors: Dr. B. EL KESSAB,C. DAOUI,K. MORO,B. BOUIKHALENE,M. FAKIR (PhD/Dr. count: 1)

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Publish Date: 2011 08, Mon

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Total Views: 5.5K

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