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Arabic Sign Language Recognition. Mohamed Mohandes King Fahd University of Petroleum and Minerals OUTILNE. Introduction Sign Language Recognition Translation of text to sign language Conclusion and future work. Importance of Sign Language.

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Arabic sign language recognition

Arabic Sign Language Recognition

Mohamed Mohandes

King Fahd University of Petroleum and Minerals


  • Introduction

  • Sign Language Recognition

  • Translation of text to sign language

  • Conclusion and future work

Importance of sign language
Importance of Sign Language

  • Arabic sign language (ARSL) is different from spoken Arabic language in terms of grammars, vocabulary, and delivery.

  • ARSL is the natural language for deaf like spoken language to vocal

  • Sign language is different from country to other (Australia, UK, USA)

  • 100,000 deaf and hearing impaired in KSA


Using Computers to make life of deaf easier and integrating them in the society :

  • Translating ARSL to spoken language

  • Translating Arabic speech to ARSL

Arsl recognition
ARSL Recognition

  • Image based

    • Requires special set up for camera

    • Heavy computational load to extract hands

  • Electronic-Glove based

    • Inconvenience of gloves

    • Ease of signal extractions


  • 22 sensors

  • Light weight

  • Flexible

Arabic sign language recognition

Coordinates of wordمع السلامة

Coordinates of word الله

Arabic sign language recognition

الاشارات المعتمدة

المنظمة العربية

للتربية والثقافة والعلوم

الاتحاد العربي

للهيئات العاملة في رعاية الصم

Arabic sign language recognition

1300 signs

344 single


Arabic sign language recognition

Data Collection

344 single handed signs

6880 Samples

6880 samples

20 samples from every sign: 15 for training and 5 for testing

System performance
System Performance

  • Time segments and Principle Component Analysis for feature extraction

  • Correct recognition rate of 98.33%

Analysis of misclassified signs
Analysis of Misclassified Signs

Frames of sign of letter “س”

Frames of sign of letter “ش”

Analysis of misclassified signs1
Analysis of Misclassified Signs

Frames from the sign “employee”

Frames from the sign “Down syndrome”

Analysis in feature space
Analysis in Feature space

Hand shape of “employee”

Hand shape of “Down syndrome”

Translating speech to arsl
Translating Speech to ARSL



Conclusions and future work
Conclusions and Future work

  • Developed a Real-time single-handed Arabic sign language recognition system with accuracy of 98.33%

  • Working on two-handed signs recognition

  • Developing our own smart glove for Arabic Sign Language

  • Mapping of signs to roots for speech to sign translation