Text recognition and face detection aid for visually impaired person using raspberry pi

 Improvement  the ability of humans who are blind or have some visual harm to independently access, understand, and explore unknown indoor and outdoor environments, we have idea a new framework using a single camera to detect and recognize the environments signs and recognize the text and

Project Title

Text recognition and face detection aid for visually impaired person using raspberry pi

Project Area of Specialization

Artificial Intelligence

Project Summary

 Improvement  the ability of humans who are blind or have some visual harm to independently access, understand, and explore unknown indoor and outdoor environments, we have idea a new framework using a single camera to detect and recognize the environments signs and recognize the text and generate output in the form of audio by suing head set system. Camera is in front of environment to judge the indoor and outdoor signs for visual impaired persons.  We can also use in agriculture automation systems to detect the leafs that are victim by any deses and also to detect the growth of the trees and leafs of trees in agriculture system. Also help in home and offices In order to find different rooms ( office rooms, or a bathroom) and other buildings  ( exit or an elevator), involved this door detection with text recognition. First they create a robust and efficient model to detect doors and elevators based on general geometric shape, by combining edges and corners. The model is generic enough to handle large intra-class variations of the object model between different indoor environments, as well as small inter-class differences between different objects such as doors and elevators.  In this model we use Raspberry Pi 3 Model B is the third generation Raspberry Pi. This powerful credit-card sized and with specifications include memory ,processor, audio output, video output and power etc. and Logitech camera with its specifications. Head set is also a part of that model. We have proposed a design on face and text recognition based on raspberry pi which is mainly designed for the purpose of blind navigation. Our future work will focus on detecting the emotions of the persons and recognizing more types of indoor objects and icons on signage in addition to text for indoor way finding aid to assist blind people travel independently. We will also study the significant human interface issues including auditory output and spatial updating of object location, orientation, and distance. With real-time updates, blind users will be able to better use spatial memory to understand the surrounding environment, obstacles and signs.

Project Objectives

The main objective of this project to provide help to the visually impaired person. By using this project impaired person known the indoor and out door environment and live independent , no required help of other person to travel. Optical character recognition (OCR) is the identification of printed characters using photoelectric devices and computer software. It coverts images of typed, handwritten or printed text into machine encoded text from scanned document or from subtitle text superimposed on an image. In this project text images are converted into audio output. OCR is used in machine process such as cognitive computing, machine translation, text to speech, key data and text mining. It is mainly used in the field of research in Character recognition, Artificial intelligence and computer vision .In this project, as the recognition process is done using OCR the character code in text files are processed using Raspberry Pi device which it recognizes character using  algorithm and python programming and audio output is listened. To use OCR for pattern recognition to perform Document image analysis (DIA) we use information in grid format in virtual digital library’s design and construction. This work mainly focuses on the OCR based automatic book reader for the visually impaired using Raspberry PI. The main objective of this model is to help blind persons by guiding them using this system . It recognizes the face, signs, obstacles, humans such as known and unknown  persons will be identified using face and text recognition features. It gives the scanned and recognized images in the form of audio output to help and guide the blind person. It is specially designed to blind navigation purpose. And other objectives is Camera-based analysis of text and documents Here they proposed a camera-based assistive framework to help blind persons to read text labels from cylinder objects in their daily life. First, the object is detected from the background or other surrounding objects in the camera view by shaking the object. Then we propose a mosaic model to unwrap the text label on the cylinder object surface and reconstruct the whole label for recognizing text information. This model can handle cylinder objects in any orientations and scales. The text information is then extracted from the unwrapped and flatted labels. The recognized text codes are then output to blind users in speech. Experimental results demonstrate the efficiency and effectiveness of the proposed framework from different cylinder objects with complex backgrounds.  We can also use in agriculture automation systems to detect the leafs that are victim by any deses and also to detect the growth of the trees and leafs of trees in agriculture system. The future enhancements are  Human emotions can be preprogrammed in order to guide blind peoples.  Unknown persons can be identified to great extent.

Project Implementation Method

Optical character recognition (OCR) is the identification of printed characters using photoelectric devices and computer software. It coverts images of typed, handwritten or printed text into machine encoded text from scanned document or from subtitle text superimposed on an image. In this project text images are converted into audio output. OCR is used in machine process such as cognitive computing, machine translation, text to speech, key data and text mining. It is mainly used in the field of research in Character recognition, Artificial intelligence and computer vision .In this project, as the recognition process is done using OCR the character code in text files are processed using Raspberry Pi device which it recognizes character using  algorithm and python programming and audio output is listened. To use OCR for pattern recognition to perform Document image analysis (DIA) we use information in grid format in virtual digital library’s design and construction. This work mainly focuses on the OCR based automatic book reader for the visually impaired using Raspberry PI. The initial phase in which a device is moved over the printed page were the camera  captures the pictures  of the  content. The nature of the picture captured will be high in order to have quick and clear recognition because of the high definition camera. In  pre-processing  Skew  Correction,  Linearization  and  Noise removal was carried out in which the captured picture is checked for  skewing. After preprocessing then devide the text and image into different segments. It is a process that breaks down a scanned image  of  sequence  to  characters  into  sub-images  of  individual symbol  (letters). And then extract given part to study. In this  stage the  perceived content  present in the  scanned image are  separated  utilizing  OCR  engines.  Here  we  utilize  tesseract OCR engine which separates the recognized characters.

Benefits of the Project

processor is raspberry pi is a fully functional linux computer and also compact in size. In field of agriculture use this model to eliminate the human resources and as well as less cost compairing with the cost of using buy the human resources. Low cost . and have most important benefit is to automatically judge the environment and solution on the base of knowledge.

Less cost required.

Eliminate the human resources.

Improvements to travel for blind person.

Eliminate the help of other to blind.

Independent to the visually impaired person use by this model.

Opportunity to read for blind person.

Opportunity to increase the knowledge for blind person.

Technical Details of Final Deliverable

Improvement  the ability of humans who are blind or have some visual harm to independently access, understand, and explore unknown indoor and outdoor environments, we have idea a new framework using a single camera to detect and recognize the environments signs and recognize the text and generate output in the form of audio by suing head set system. Camera is in front of environment to judge the indoor and outdoor signs for visual impaired persons. The main objective of this project to provide help to the visually impaired person. By using this project impaired person known the indoor and out door environment and live independent , no required help of other person to travel. Optical character recognition (OCR) is the identification of printed characters using photoelectric devices and computer software. processor is raspberry pi is a fully functional linux computer and also compact in size. In field of agriculture use this model to eliminate the human resources and as well as less cost compairing with the cost of using buy the human resources. Low cost . and have most important benefit is to automatically judge the environment and solution on the base of knowledge. The initial phase in which a device is moved over the printed page were the camera  captures the pictures  of the  content. The nature of the picture captured will be high in order to have quick and clear recognition because of the high definition camera. In  pre-processing  Skew  Correction,  Linearization  and  Noise removal was carried out in which the captured picture is checked for  skewing. After preprocessing then devide the text and image into different segments. It is a process that breaks down a scanned image  of  sequence  to  characters  into  sub-images  of  individual symbol  (letters). And then extract given part to study. In this  stage the  perceived content  present in the  scanned image are  separated  utilizing  OCR  engines.  Here  we  utilize  tesseract OCR engine which separates the recognized characters. Requirements is USB camera, Raspberry pi 3 Model B, LCD Display, capacitors, Transistors, Cables & Connectors, Diode,  PCB circuit boards, LEDs and transformer/Adaptor.

Final Deliverable of the Project

HW/SW integrated system

Core Industry

Others

Other Industries

Education , Agriculture , Security

Core Technology

Artificial Intelligence(AI)

Other Technologies

Cloud Infrastructure, Others

Sustainable Development Goals

Partnerships to achieve the Goal

Required Resources

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