Raspberry pi based reader for blind people

In this project we are making document reader for visually impaired people, developed on Raspberry Pi. It uses the Optical character recognition technology for the identification of the printed characters using image sensing devices and computer programming. It converts images of typed, handwri

Project Title

Raspberry pi based reader for blind people

Project Area of Specialization

Electrical/Electronic Engineering

Project Summary

In this project we are making document reader for visually impaired people, developed on Raspberry Pi. It uses the Optical character recognition technology for the identification of the printed characters using image sensing devices and computer programming. It converts images of typed, handwritten, or printed text into machine encoded text. In this research these images are converted into the audio output (Speech) audio output is achieved.

Project Objectives

 Character Recognition has become main aspect of Computer vision. Optical Character Recognition is a method where characters are recognized from images digitally. In this project an innovative, efficient and real-time cost beneficial technique that enables user to hear the contents of text images instead of reading through them has been introduced. Text-to-Speech converter is a device that scans and reads English alphabets in the image using OCR technique and changing it to voices. It combines the concept of Optical Character Recognition (OCR) and Text to Speech Synthesizer (TTS) in Raspberry pi. This kind of system helps visually impaired people to interact with computers effectively through vocal interface. Text Extraction from color images is a challenging task in computer vision. This project describes the design, implementation and experimental results of the device. This device consists of two modules, image processing module and voice processing module.

Project Implementation Method

In this system, the printed text is to be placed under the camera view by the blind person to ensure the image of good quality and fewer distortions. Then an applicable blindassistive system, a text localization algorithm might prefer higher recall by sacrificing some precision. When the application starts at first, it checks the availability of all the devices and also for the connection. The GUI displays the status of the image clicked from the camera and a status box for representing the image. The Raspberry Pi has integrated peripheral devices like USB, ADC, Bluetooth and Serial.

The operating system under which the proposed project is executed is Raspbian which is derived from the Debian operating system. The algorithms are written using the python language which is a script language. The functions in algorithm are called from the OpenCV Library. OpenCV is an open source computer vision library, which is written under C and C++ and runs under Linux, Windows and Mac OS X. OpenCV was designed for computational efficiency and with a strong focus on real-time applications. OpenCV is written in optimized C and can take advantage of multi-core processors.The operating system under which the proposed project is executed is Raspbian which is derived from the Debian operating system.As the recognition process is completed, the character codes in the text file are processed using Raspberry Pi device on which recognize a character using Tesseract algorithm and python programming, the audio output listens. 

Benefits of the Project

It can save time of users by reading more data at a time than earlier system.

Earlier system concise to specific writing style but proposed system will present 2 to 3 writing styles and fonts.

Blind people can hear more documents in less time efficiently.

In this project an innovative, efficient and real-time cost beneficial technique that enables user to hear the contents of text images instead of reading through them has been introduced.

Technical Details of Final Deliverable

When capture button is clicked, this system captures the document image placed in front of the camera which is connected to ARM microcontroller through USB .After selecting the process button the captured document image undergoes Optical Character Recognition(OCR) Technology. OCR technology allows the conversion of scanned images of printed text or symbols into text or information that can be understood or edited using a computer program. In our system for OCR technology we are using TESSERACT library. Using Text-to-speech library the data will be converted to audio. Camera acts as main vision in detecting the image of the placed document, then image is processed internally and separates label from image by using open CV library and finally identifies the text which is pronounced through voice. Now the converted text into audio output is listened either by connecting headsets via 3.5mm audio jack or by connecting speakers via Bluetooth.

Raspberry Pi is a low cost, credit card sized computer that plugs into computer monitor or TV and uses standard keyboard and mouse.There are two models of it, Raspberry Pi 2 and Raspberry Pi 3. 

The hardware components of the Raspberry Pi include power supply, storage, input, monitor and network. Power Supply Unit is the device that supplies electrical energy to the output loads. It gives a well regulated power supply of +5v with a output current compatibility of 100 mA. Camera feeds its images in real time to a computer or computer network, often via USB, Ethernet or Wi-Fi. HDMI to VGA Converter is used to connect the Raspberry Pi board to the Projectors, Monitors and TV.

SOFTWARE IMPLEMENTATION Operating system: Raspbian (Debian) Language: Python2.7 Platform: Tesseract, OpenCV (Linux-library) Library: OCR engine, TTS engine The operating system under which the proposed project is executed is Raspbian which is derived from the Debian operating system. The algorithms are written using the python language which is a script language. The functions in algorithm are called from the OpenCV Library. OpenCV is an open source computer vision library, which is written under C and C++ and runs under Linux, Windows and Mac OS X. OpenCV was designed for computational efficiency and with a strong focus on real-time applications. OpenCV is written in optimized C and can take advantage of multi-core processors. 

The ASCII values of the recognized characters are processed by Raspberry Pi board. Here each of the characters is matched with its corresponding template and saved as normalized text transcription. This transcription is further delivered to the audio output.

Final Deliverable of the Project

HW/SW integrated system

Core Industry

IT

Other Industries

Telecommunication

Core Technology

Others

Other Technologies

Sustainable Development Goals

Good Health and Well-Being for People

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com