Evaluation of Features Extraction and Classification Techniques for Offline Handwritten Tifinagh Recognition

Mouhcine Rabi; Mustapha Amrouch

Evaluation of Features Extraction and Classification Techniques for Offline Handwritten Tifinagh Recognition

Mouhcine Rabi *

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Mustapha Amrouch

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Evaluation of Features Extraction and Classification Techniques for Offline Handwritten Tifinagh Recognition

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Abstract

This paper presents a review on different features extraction and classification methods for off-line handwritten Amazigh characters (called Tifinagh) recognition. The features extraction methods are discussed based on Statistical, Structural, Global transformation and moments.Although a number of techniques are available for feature extraction and classification,but the choice of an excellent technique decides the degree of accuracy of recognition. A series of experimentswere performed on AMHCD databaseallowing to evaluate the effectiveness of different techniques of extraction features based on Hidden Markov models, Neural network and Support vector Machine classifiers. The statistical techniques giveencouraging results.

References

9 Cites in Article

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1. B Qacimya,M Hammouch,Kerroum (2015). A review of feature extraction techniques for hand written Arabic text recognition. Electrical and Information Technologies (ICEIT)
2. S Arora1,D Bhattacharjee2,M Nasipuri2,D Basu2,M Kundu2 (2010). Application of Statistical Features in Handwritten Devnagari Character Recognition. Application of Statistical Features in Handwritten Devnagari Character Recognition
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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

Mouhcine Rabi, Mustapha Amrouch. 2017. "Evaluation of Features Extraction and Classification Techniques for Offline Handwritten Tifinagh Recognition". Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 16 (GJCST Volume 16 Issue C5).

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GJCST Volume 16 Issue C5

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

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Classification

D.3.4

F.4.2

Submission ReceivedDecember 11, 2015
Peer Review Double Blind
Handling Editor
Accepted January 5, 2016
Published January 15, 2016

Version of record

v1.2

Issue date

January 27, 2017

Language

English

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Article Matrices

Total Score: 123

Country: Morocco

Subject: Global Journal of Computer Science and Technology - C: Software & Data Engineering

Authors: Mouhcine Rabi, Mustapha Amrouch, Zouhir Mahani (PhD/Dr. count: 0)

View Count (all-time): 540

Total Views (Real + Logic): 1598

Total Downloads (simulated): 90

Publish Date: 2016 01, Fri

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Total Views: 1.6K

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