Introduction: Sign Language Translation Into Text
The deaf and mute are considered a class and a part of society, and they need easy and quick communication with all members of society anywhere.
So our project is the use of artificial intelligence in order to translate the hand movement through the camera and it is translated into text on the screen, which makes communication easier, faster and clearer between the deaf and the mute and other members of society.
Supplies
1- Raspberry pi 4 (8GB RAM) Kit.
2- 7 Inch Touchscreen for Raspberry Pi 4, 1024 x 600 HD Display Touch Screen.
3- Webcam full HD.
4- Laptop stand.
Step 1: Raspbian Installation on Raspberry Pi
First, you must install the system running the Raspberry pi (Raspbian)
Step 2: Install Python 3
We need to install python 3 because the project works with python 3
This video explains how to install python 3 on Raspberry pi
Step 3: Install Open SV
We will use open cv library for object detection Because we want to use it to read palm movement.
Install method and steps :
Step 4: Install Hand Detector Code
After install open SV we installed hand detector code from https://github.com/Shubhamai/face-hand-detector
Step 5: Install Hand Gesture Recognition Code
We need to install Hand Gesture Recognition code because the project idea is Reading the hand movement of the deaf and mute and converting it into a text
Source of the code
Step 6: Assembly and Final Design
After making sure that the project works well, we connect the project parts together and make the final design of the project.
Step 7: Difficulties and Solutions
Install Tensor Flow Library
The solution is to replace it with open CV library
Step 8: Video of the Project
Step 9: Thanks and Appreciation
Our sincere thanks and gratitude to Dr. Jaber Al-Yamani for his support and guidance that helped us in the completion of this project, and we also thank the College of Telecom and Electronics for all the assistance and guidance provided to us.
Thank you very much
