Smart Blind Gloves

The main aim of this project is to contribute in the assistance of the visually impaired people making them independent of a braille reading system or a digital speech synthesizer as these facilities are not always available everywhere and for everyone. These individuals are hindered from a norm

Project Title

Smart Blind Gloves

Project Area of Specialization

Internet of Things

Project Summary

The main aim of this project is to contribute in the assistance of the visually impaired people making them independent of a braille reading system or a digital speech synthesizer as these facilities are not always available everywhere and for everyone. These individuals are hindered from a normal life and wages. An advanced step towards convenience and portability promises an easier and furthermore much interesting life. The speech assistant can help them perform many day to day tasks like normal people such as reading a sign board or any important document which can give them more exposure of this world.

Without vision it can be challenging for a visually impaired person to  read a book and

other documents, Blind people has less opportunity as compared to normal people to improve their  educational skills, Blind people depends on companion to go out side. This project can make the life of Visually Challenged People more interesting and easier as they can perform many tasks like normal people such as reading a board or document which can give them more exposure of this world.

Project Objectives

This project can make the life of Visually Challenged People more interesting and easier as they can perform many tasks like normal people such as reading a board or document which can give them more exposure of this world.

1. To detect text from Natural Scene as well as documents and papers with much accuracy.
2. To extract appropriate ROI of detected text and performing Image Processing.
3. To Implement Optical Character Recognition (OCR) and recognizing words, sentences, characters and numbers.
4. To make OCR more efficient by recognizing text from written text and documents.

To remove as much noise as possible and obtain machine-coded text.

This project can make the life of Visually Challenged People more interesting and easier                   as they can perform many tasks like normal people such as reading a board or document which can give them more exposure of this world.

1. To detect text from Natural Scene as well as documents and papers with much accuracy.
2. To extract appropriate ROI of detected text and performing Image Processing.
3. To Implement Optical Character Recognition (OCR) and recognizing words, sentences, characters and numbers.
4. To make OCR more efficient by recognizing text from written text and documents.
5. To remove as much noise as possible and obtain          machine-coded text.
6.  
7. To implement TTS Method in order to convert machine-coded text into Voice using Raspberry Pi.
8. To make the system more efficient by reading different words, characters, numbers, sentences, and paragraph. 
9. To develop a systematic way of performing each task with proper procedure that can assist a Visually Impaired Person.
10. To design and develop a device that can be carried by Visually Impaired People with the connection of Camera in an appropriate place.
11. To make a user friendly and affordable device.

Project Implementation Method

1. 1. Operating Environment

 Consolidates the 13 idea of optical character recognition (OCR) and text to speech synthesizer (TTS) in Raspberry pi. This type of system encourages the blind to associate themselves with computers in a viable way through the vocal interface. Extracting text from color images is a difficult task in computer vision. Text-to-speech is a strategy that scans and examines English letters in order and numbers in the image, using the OCR method and turning them into voices. This document describes the plan, usage and after-effects of testing the gadget.

OCR Using Raspberry Pi for The Visually Impaired.

Optical character recognition (OCR) is the distinctive proof of characters printed using photoelectric devices and computer software. It converts images of compound text, written manually or printed into machine-encoded text from a scanned document or caption text overlaid on an image. In this project, text images are transformed into sound production. OCR is used in a machine cycle, for example, cognitive computing, machine translation, text to speech, text mining of key information ads. It is mainly used in the field of character recognition research, artificial intelligence and computer vision. In this project, when the recognition cycle is completed using OCR, the character codes in text

records are prepared using the raspberry pi gadget in which it perceives the character using the tesseract algorithm and python programming and sound performance are activated. To use OCR for pattern recognition analysis of document images (DIA) we use information in a grid format when planning and developing the virtual digital library. This work revolves mainly around the OCR-based automatic book reader for the blind using raspberry pi.

Pi Camera

The Raspberry Pi Camera Module v2 replaced the original Camera Module in April 2016. The v2 Camera Module has a Sony IMX219 8-megapixel sensor (compared to the 5-megapixel OmniVision OV5647 sensor of the original camera).

The Camera Module can be used to take high-definition video, as well as stills photographs. It’s easy to use for beginners, but has plenty to offer advanced users if you’re looking to expand your knowledge. There are lots of examples online of people using it for time-lapse, slow-motion, and other video cleverness. You can also use the libraries we bundle with the camera to create effects.

You can read all the gory details about IMX219 and the Exmor R back-illuminated sensor architecture on Sony’s website, but suffice to say this is more than just a resolution upgrade: it’s a leap forward in image quality, colour fidelity, and low-light performance. It supports 1080p30, 720p60 and VGA90 video modes, as well as still capture. It attaches via a 15cm ribbon cable to the CSI port on the Raspberry Pi.

Benefits of the Project

1. 1. Performance Requirements

Performance requirements of smart blind glove perform different phases with  some different functionalities:
These functionalities were listed below:

1. Usability

Usability of smart blind gloves can read urdu text and english  text  as well easily  in

Run time.

1. Authentication and Authorization

Authentication of smart blind gloves is not need any user id or password for use everyone can use it freely.

1. Maintainability
   The smart blind glove must be easy to modify and maintain.
2. Effectiveness
   Smart blind glove is help to blind people to make their reading skill effective.
3. Interoperability
   Smart blind glove should be able to connect for the user easily.
4. Efficiency

Smart blind glove gives accurate result within time.

Technical Details of Final Deliverable

1. The natural scene text detection is achieved, enabling a blind person to detect text around him very accurately and efficiently at a distance of 4ft to 5ft and less.
2. Appropriate ROIs are extracted of detected text and Image processing is done with much competence.
3. The use of optical character recognition is achieved by enabling the device to be able to read documents or typed black text on white background with much accuracy.
4. The device is made efficient such that it can read and recognize text as well as characters and numbers both separately.
5. The device offers two components: a non-mobile wooden box which enables a visually impaired person to read any documents or text. It is very easy to use and gives instructions in audio output. The device notifies you when it takes a picture and then read the text. Hence making a blind person read a text without any dependency.
6. The wearable glasses are portable and easy to carry. A belt is attached with the glasses. The wearable glasses will help the blind person to detect any text around him.
7. The device is made efficient since it can detect and recognize 3 basic font styles with much accuracy i.e. Arial, times new roman and Calibri. Also, fonts similar to these with a basic structure can also be read easily.
8. The efficiency is further increased by enabling the devise to read smaller font size. It can much accurately detect and read font size 14 and above.

Final Deliverable of the Project

HW/SW integrated system

Core Industry

Education

Other Industries

Medical , Health

Core Technology

Internet of Things (IoT)

Other Technologies

Artificial Intelligence(AI), Robotics

Sustainable Development Goals

Quality Education

Required Resources

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