Description

Abstract

Assistive technologies are being developed for deaf and dump people in order to live confidently. This project work proposes a camera-based assistive gesture reading framework to help blind persons to read text labels. Here we are using 16 sign detection, Functions of each sign can be easily configurable to certain process (ex: For any voice command, asking for some needs or typing any letters, etc.,) using the hand sign which is detected using a camera and sign detection is done using OpenCV.

---

Introduction

The Raspberry Pi is a credit card sized single computer or SoC uses ARM1176JZF-S core. SoC, or System on a Chip, is a method of placing all necessary electronics for running a computer on a single chip. Instead of having an individual chip for the CPU, GPU, USB controller, RAM everything is compressed down into one tidy package. Raspberry Pi needs an Operating system to start up. In the aim of cost reduction, the Raspberry Pi omits any on-board non-volatile memory used to store the boot loaders. We are using OpenCV to process the captured image to detect the sign.

---

Existing system

Existing system uses the only simulation platform, to process the image for signature detection.

---

Proposed system

This project work proposes a camera-based assistive sign detection and processing some functions like audio request or text using Raspberry Pi. Normally in deaf and dump schools they are using sign language for their communication, likewise here we are using 16 signs recognition and processing some functions.

---

Advantage

Mainly used for deaf and dump peoples, if they show some signs, each sign does some functions like audio output or text output. 

---

Block diagram

---

Block diagram description

In the above block diagram the whole system is controlled by Arm11  processor  and  this  processor  is  implemented  on the Raspberry Pi Board.    The system consists of Raspberry pi, Camera, SD card and a personal computer. Those all components are connected by USB adapters. Raspberry pi is the key element in processing module. First sign has been detected using USB camera, then it performs the functions which are pre-configured for every sign.

---

Circuit diagram

---

Component used

• Raspberry Pi
• Mini Camera
• SD card
• Monitor
• USB adapters
• Audio Output unit

---

Software used

• Raspbian Jessie OS
• Python
• Open CV
• Apache
• PHP

---

Applications

Normally sign language is used for deaf persons, By this project, it performs the text output for deaf people and audio output for the blind using the sign language

---

Conclusion

Generally theory shows that there are 69 sign languages are there, whereas it also includes the motion in the head is also having some sign functions. We can also configure this system for every sign which are used by the deaf and dump peoples.