The document discusses a project to develop a desktop application that converts sign language to speech and text to sign language. It aims to help communicate with deaf people by removing barriers. The team plans to use EmguCV and C# Speech Engine. It has created an application that converts signs to text using image processing. Future work includes completing the software to cover all words in Arabic sign language.

1. Hand Gesture Recognition
Under The Supervision of
Prof. Aliaa Abdel-Halim Abdel-Razik Youssif

2. Bringing them to us!
 Imagine your self a Deaf Person
 How would you express your feelings, thoughts and
ideas.
 Will you be able to deliver them right and easily.

3. We need them !
 As the handicap people representing a large scale of our
community we should take steps to be able to
communicate with them to share knowledge ,thoughts
,ideas and even feelings.
 So we want to create a communication mean that we
can use to do so.

4. Team members
 Ahmed Abdel-Aziz El-Said El-Gazzar.
 Ahmed Osama Ahmed Fouad.
 Amr Muhammed Abou-Elgood.
 Karim Nabil Ibrahim.
 Muhammed Magdy Mekki.
 Sharif Ahmed Abdel-Sattar.

5. Agenda
 Intro
 Project Idea
 Why ?!
 Technical Overview
# Tools & IDE.
# Previous work
# Currant state
 Project Scenario
 Conclusion

6. Project Idea
 Desktop application.
 Converting sign language into speech and
convert text to sign language.
 Using intermediate phase (text).

7. Why?!
 Because we need Deaf Persons in
our society .
 Also to remove all the
communication barriers between us.
 For deaf people to be able to live a normal
happy life.

8. Technical overview
 Tools
• EmguCV
It is the .NET OpenCV
library
• C# Speech Engine.
the tool that we used to
convert the text to Speech
 IDE
• Microsoft Visual Studio .
• Open CV on MVS.

9. Technical overview (cont’d)
 Previous work
• Developing C# program that converts the text into
speech and vice versa using C# speech Engine.
• Searching about MATLAB & OPEN CV.
• Self studying image processing & Machine
Learning Development.

10. Technical overview (cont’d)
 Currant state
• an application that converts from sign
language to Text using Emgu CV.

11. Project Scenario
Sign Speech
Draw your
Hand Sign

12. Project Scenario(cont’d)
Use case: Sign Detection.
Brief Description:
The deaf person act the sign that represent a specific phrase or word.
Initial Step-By-Step Description:
Before this use case can be initiated, the Application already running
and the deaf person must be standing at appropriate distance from the
camera.
1- The deaf person stands at appropriate distance from the camera.
2- The application is set to sign detection mode.
3- The system plays the speech representing the sign detected.

13. Project Scenario(cont’d)
Speech Sign
Select Phrase

14. Project Scenario(cont’d)
Use case: Sign Drawing.
Brief Description:
The normal person select the Phrase then the application draws the
sign.
Initial Step-By-Step Description:
Before this use case can be initiated, the Application already running .
1- The normal person select the Sign Text (Phrase) .
2- The application convert the text into sign language.
3- The system plays the sign video appropriate to the Selection
detected.

15. Project Scenario
 Sign To Speech way .
The form Divided in two Parts .
 Left Part use convex Hull algorithm
to detect corner points and
calculate them by K-curvature
angle.
 Right Part use Polygon method and
do the previous steps.

16. Project Scenario
 Text To Sign way .
 I n the second way You can choose
the Phrase (Alphabets or Numbers
or Phrases ) you need to translate
it to sign and view its video .

17. Conclusion
 We Presented The Implementation of a
System That aims to Translate sign language
(Hand Gestures) into speech (Sound).
 In the future we aspire to Complete software
application that will be available commercially
to users that have a fast Mobile, a camera,
and speakers and cover all words in Arabic
sign language.