Dynamic Hand Gesture Recognition of Arabic Sign Language using Hand Motion Trajectory Features

Dynamic Hand Gesture Recognition of Arabic Sign Language using Hand Motion Trajectory Features

Mohamed sameer Mohamed Abdalla

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Mohamed S. Abdalla

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Elsayed E. Hemayed

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Cairo University

Dynamic Hand Gesture Recognition of Arabic Sign Language using Hand Motion Trajectory Features

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Abstract

In this paper we propose a system for dynamic hand gesture recognition of Arabic Sign Language. The proposed system takes the dynamic gesture (video stream) as input, extracts hand area and computes hand motion features, then uses these features to recognize the gesture. The system identifies the hand blob using YCbCr color space to detect skin color of hand. The system classifies the input pattern based on correlation coefficients matching technique. The significance of the system is its simplicity and ability to recognize the gestures independent of skin color and physical structure of the performers. The experiment results show that the gesture recognition rate of 20 different signs, performed by 8 different signers, is 85.67%.

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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

Mohamed sameer Mohamed Abdalla. 2013. \u201cDynamic Hand Gesture Recognition of Arabic Sign Language using Hand Motion Trajectory Features\u201d. Global Journal of Computer Science and Technology - F: Graphics & Vision GJCST-F Volume 13 (GJCST Volume 13 Issue F5).

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GJCST Volume 13 Issue F5

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

arabic sign language correlation coefficients Face detection Gesture recognition hu moments skin color segmentation

Submission ReceivedDecember 11, 2012
Peer Review Double Blind
Handling Editor
Accepted December 31, 2012
Published January 15, 2013

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v1.2

Issue date

June 29, 2013

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Article Matrices

Total Score: 102

Country: Egypt

Subject: Global Journal of Computer Science and Technology - F: Graphics & Vision

Authors: Mohamed S. Abdalla, Elsayed E. Hemayed (PhD/Dr. count: 0)

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Publish Date: 2013 06, Sat

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Total Views: 9447

Total Downloads: 2392

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