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

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Mouhcine Rabi
Mouhcine Rabi
2
Mustapha Amrouch
Mustapha Amrouch
3
Zouhir Mahani
Zouhir Mahani

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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.

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No external funding was declared for this work.

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The authors declare no conflict of interest.

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No ethics committee approval was required for this article type.

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Mouhcine Rabi. 2017. \u201cEvaluation of Features Extraction and Classification Techniques for Offline Handwritten Tifinagh Recognition\u201d. 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
Pg. 37- 42
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Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords
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D.3.4,F.4.2
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January 27, 2017

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English

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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.

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

Mouhcine Rabi
Mouhcine Rabi
Mustapha Amrouch
Mustapha Amrouch
Zouhir Mahani
Zouhir Mahani

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