Recognition of Cursive Arabic Handwritten Text using Embedded Training based on HMMs

Recognition of Cursive Arabic Handwritten Text using Embedded Training based on HMMs

Mouhcine Rabi

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Recognition of Cursive Arabic Handwritten Text using Embedded Training based on HMMs

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Abstract

In this paper we present a system for offline recognition cursive Arabic handwritten text based on Hidden Markov Models (HMMs). The system is analytical without explicit segmentation used embedded training to perform and enhance the character models. Extraction features preceded by baseline estimation are statistical and geometric to integrate both the peculiarities of the text and the pixel distribution characteristics in the word image. These features are modelled using hidden Markov models and trained by embedded training. The experiments on images of the benchmark IFN/ENIT database show that the proposed system improves recognition.

References

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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. 2016. \u201cRecognition of Cursive Arabic Handwritten Text using Embedded Training based on HMMs\u201d. Global Journal of Computer Science and Technology - D: Neural & AI GJCST-D Volume 16 (GJCST Volume 16 Issue D1): .

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GJCST Volume 16 Issue D1
Pg. 27- 31

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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

GJCST-D Classification: I.3.3, I.4.10

Submission ReceivedDecember 15, 2015
Peer Review Double Blind
Handling Editor
Accepted December 31, 2015
Published January 15, 2016

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v1.2

Issue date

December 16, 2016

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Article Matrices

Total Score: 121

Country: Morocco

Subject: Global Journal of Computer Science and Technology - D: Neural & AI

Authors: Mouhcine Rabi (PhD/Dr. count: 0)

View Count (all-time): 247

Total Views (Real + Logic): 7341

Total Downloads (simulated): 1811

Publish Date: 2016 12, Fri

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Total Views: 7341

Total Downloads: 1811

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