The technology is growing vastly. Everyone in humanity has some limitations. One of those limitations is visual disability. So we are here with a system that helps the visually disabled people. The framework here contains object detection with voice assistance within an app and a hardware part attached to the blinds stick for distance calculation. The app is designed to support the blind person to explore freely anywhere he wants. The working of the framework begins by surveilling the situations around the user and distinguishing them utilizing a camera. The app will then detect the objects present in the input video frame by using the SSD algorithm comparing it with the trained model. The video captured is partitioned into grids to detect the object obstacle. In this way, the subtleties of the object detected can be achieved and along with it distance measurement can also be calculated using specific algorithms. A Text to Speech TTS converter is utilized for changing over the data about the object detected into an audio speech format. The framework application passes on the scene which the blind people is going in his her territorial language with the snap of a catch. The technologies utilized here makes the framework execution effective. Sabin Khader | Meerakrishna M R | Reshma Roy | Willson Joseph C "Godeye: An Efficient System for Blinds" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-4 , June 2020, URL: https://www.ijtsrd.com/papers/ijtsrd31631.pdf Paper Url :https://www.ijtsrd.com/engineering/computer-engineering/31631/godeye-an-efficient-system-for-blinds/sabin-khader
Face is a complex multidimensional visual model and developing a computational model for face recognition is difficult. The paper presents a methodology for face recognition based on information theory approach of coding and decoding the face image. The goal is to implement the system model for a particular face and distinguish it from a large number of stored faces with some real-time variations as well. The Eigenface approach uses Principal Component Analysis PCA algorithm for the recognition of the images. It gives us efficient way to find the lower dimensional space. In todays world, face recognition is an important part for the purpose of security and surveillance. Hence there is a need for an efficient and cost effective system. Our goal is to explore the feasibility of implementing Raspberry Pi based face recognition system using conventional face detection and recognition techniques such as Haar detection and PCA. This paper aims at taking face recognition to a level in which the system can replace the use of passwords and RF I-Cards for access to high security systems and buildings. With the use of the Raspberry Pi kit, we aim at making the system cost effective and easy to use, with high performance. Amit Deshwal | Mohnish Chandiramani | Umesh Jagtap | Prof. Amruta Surana "Smart Door Access using Facial Recognition" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-2 , February 2019, URL: https://www.ijtsrd.com/papers/ijtsrd21363.pdf
Paper URL: https://www.ijtsrd.com/computer-science/artificial-intelligence/21363/smart-door-access-using-facial-recognition/amit-deshwal
Face recognition smart cane using haar-like features and eigenfacesTELKOMNIKA JOURNAL
Visually impaired has the limitation in interacting with another human. They usually use the sense of hearing and touching their face to recognize human. Face recognition is a technology that can be used to solve this problem. This paper develops a smart cane function by integrated face recognition feature on the cane using Haar-Like features and Eigenfaces. This paper proposed a portable, real time, and wearable product. Raspberry Pi supports portability that affects the delay and computing speed of face recognition algorithms. Utilization of Raspi camera on the eyes glasses is for wearable purposes. Voice output provides information on whether the face is caught on camera or not. This prototype works well during the face detection and recognition process. It needs 3 seconds for one-face recognized in range 0.25 until 1.5 meters from the camera, until the sound and information are generated. It needs is me 5 second for two faces recognized and 10 seconds for 3 faces recognized by a system in the same range between face and the camera. The accuracy reaches 91.67% for the up-right position face but for other position the accuracy is only 18% until 32%.
Profile Identification through Face Recognitionijtsrd
This project is Profile identification through facial recognition system using machine learning, based on K neighbors algorithm. The K neighbours algorithm has high detection rate and fast processing time. Once the face is detected, feature extraction on the face is performed using histogram of oriented gradients which essentially stores the edges of the face as well as the directionality of those edges. Histogram of oriented gradients is an effective form of feature extraction due its high performance in normalizing local contrast. Lastly, training and classification of the facial databases is done where each unique face in the facial database is a class. We attempt to use this facial recognition system on two sets of databases and will analyse the results and then provide the profile of an individual which is written in the Data base created in Firebase. Mr. B. Ravinder Reddy | V. Akhil | G. Sai Preetham | P. Sai Poojitha ""Profile Identification through Face Recognition"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23439.pdf
Paper URL: https://www.ijtsrd.com/computer-science/other/23439/profile-identification-through-face-recognition/mr-b-ravinder-reddy
The technology is growing vastly. Everyone in humanity has some limitations. One of those limitations is visual disability. So we are here with a system that helps the visually disabled people. The framework here contains object detection with voice assistance within an app and a hardware part attached to the blinds stick for distance calculation. The app is designed to support the blind person to explore freely anywhere he wants. The working of the framework begins by surveilling the situations around the user and distinguishing them utilizing a camera. The app will then detect the objects present in the input video frame by using the SSD algorithm comparing it with the trained model. The video captured is partitioned into grids to detect the object obstacle. In this way, the subtleties of the object detected can be achieved and along with it distance measurement can also be calculated using specific algorithms. A Text to Speech TTS converter is utilized for changing over the data about the object detected into an audio speech format. The framework application passes on the scene which the blind people is going in his her territorial language with the snap of a catch. The technologies utilized here makes the framework execution effective. Sabin Khader | Meerakrishna M R | Reshma Roy | Willson Joseph C "Godeye: An Efficient System for Blinds" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-4 , June 2020, URL: https://www.ijtsrd.com/papers/ijtsrd31631.pdf Paper Url :https://www.ijtsrd.com/engineering/computer-engineering/31631/godeye-an-efficient-system-for-blinds/sabin-khader
Face is a complex multidimensional visual model and developing a computational model for face recognition is difficult. The paper presents a methodology for face recognition based on information theory approach of coding and decoding the face image. The goal is to implement the system model for a particular face and distinguish it from a large number of stored faces with some real-time variations as well. The Eigenface approach uses Principal Component Analysis PCA algorithm for the recognition of the images. It gives us efficient way to find the lower dimensional space. In todays world, face recognition is an important part for the purpose of security and surveillance. Hence there is a need for an efficient and cost effective system. Our goal is to explore the feasibility of implementing Raspberry Pi based face recognition system using conventional face detection and recognition techniques such as Haar detection and PCA. This paper aims at taking face recognition to a level in which the system can replace the use of passwords and RF I-Cards for access to high security systems and buildings. With the use of the Raspberry Pi kit, we aim at making the system cost effective and easy to use, with high performance. Amit Deshwal | Mohnish Chandiramani | Umesh Jagtap | Prof. Amruta Surana "Smart Door Access using Facial Recognition" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-2 , February 2019, URL: https://www.ijtsrd.com/papers/ijtsrd21363.pdf
Paper URL: https://www.ijtsrd.com/computer-science/artificial-intelligence/21363/smart-door-access-using-facial-recognition/amit-deshwal
Face recognition smart cane using haar-like features and eigenfacesTELKOMNIKA JOURNAL
Visually impaired has the limitation in interacting with another human. They usually use the sense of hearing and touching their face to recognize human. Face recognition is a technology that can be used to solve this problem. This paper develops a smart cane function by integrated face recognition feature on the cane using Haar-Like features and Eigenfaces. This paper proposed a portable, real time, and wearable product. Raspberry Pi supports portability that affects the delay and computing speed of face recognition algorithms. Utilization of Raspi camera on the eyes glasses is for wearable purposes. Voice output provides information on whether the face is caught on camera or not. This prototype works well during the face detection and recognition process. It needs 3 seconds for one-face recognized in range 0.25 until 1.5 meters from the camera, until the sound and information are generated. It needs is me 5 second for two faces recognized and 10 seconds for 3 faces recognized by a system in the same range between face and the camera. The accuracy reaches 91.67% for the up-right position face but for other position the accuracy is only 18% until 32%.
Profile Identification through Face Recognitionijtsrd
This project is Profile identification through facial recognition system using machine learning, based on K neighbors algorithm. The K neighbours algorithm has high detection rate and fast processing time. Once the face is detected, feature extraction on the face is performed using histogram of oriented gradients which essentially stores the edges of the face as well as the directionality of those edges. Histogram of oriented gradients is an effective form of feature extraction due its high performance in normalizing local contrast. Lastly, training and classification of the facial databases is done where each unique face in the facial database is a class. We attempt to use this facial recognition system on two sets of databases and will analyse the results and then provide the profile of an individual which is written in the Data base created in Firebase. Mr. B. Ravinder Reddy | V. Akhil | G. Sai Preetham | P. Sai Poojitha ""Profile Identification through Face Recognition"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23439.pdf
Paper URL: https://www.ijtsrd.com/computer-science/other/23439/profile-identification-through-face-recognition/mr-b-ravinder-reddy
Fontys - Demystify AI. Wat is er mogelijk met AI en wat niet?BigDataExpo
Er is een explosie van toepassingen van Neural Nets en Deep learning. Wat kunnen deze wel en wat kunnen ze niet. Wat kan deze ontwikkeling voor U betekenen?
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The software will use the camera of the device and scan all the obstacles with their corresponding distances from the user. This will be followed by audio instructions through audio output of the device.
This will efficiently direct the user through his/her way.
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One consequence of a visually impaired (blind) person is a lack of ability in the activities related to the orientation and mobility. Blind person uses a stick as a tool to know the objects that surround him/her.The objective of this research is to develop a tool for blind person which is able to recognize what object in front of him/her when he/she is walking. An attached camera will obtain an image of an object which is then processed using template matching method to identify and trace the image of the object. After getting the image of the object, furthermore calculate and compare it with the data training. The output is produced in the form of sound that in accordance with the object. The result of this research is that the best slope and distance for the template matching method to properly detect silent objects is 90 degrees and 2 meters.
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The loss of vision restrained the visually impaired people from performing their daily task. This issue has impeded their free-movement and turned them into dependent a person. People in this sector did not face technologies revamping their situations. With the advent of computer vision, artificial intelligence, the situation improved to a great extent. The propounded design is an implementation of a wearable device which is capable of performing a lot of features. It is employed to provide visual instinct by recognizing objects, identifying the face of choices. The device runs a pre-trained model to classify common objects from household items to automobiles items. Optical character recognition and Google translate were executed to read any text from image and convert speech of the user to text respectively. Besides, the user can search for an interesting topic by the command in the form of speech. Additionally, ultrasonic sensors were kept fixed at three positions to sense the obstacle during navigation. The display attached help in communication with deaf person and GPS and GSM module aid in tracing the user. All these features run by voice commands which are passed through the microphone of any earphone. The visual input is received through the camera and the computation task is processed in the raspberry pi board. However, the device seemed to be effective during the test and validation.
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Er is een explosie van toepassingen van Neural Nets en Deep learning. Wat kunnen deze wel en wat kunnen ze niet. Wat kan deze ontwikkeling voor U betekenen?
Eye(I) Still Know! – An App for the Blind Built using Web and AIDr. Amarjeet Singh
This paper proposes eye(I) still know!, a voice control solution for the visually impaired people. The main purpose is even though the blind cannot see they can still know where to go and what to do! Nearby 60% of total blind population across the world is present in India. In a time where no one likes to rely on anyone, this is a small effort to make the blind independent individuals. This can be achieved using wireless communication, voice recognition and image scanning. The application with the use of object identification will priorly inform about the barriers in the path.
The software will use the camera of the device and scan all the obstacles with their corresponding distances from the user. This will be followed by audio instructions through audio output of the device.
This will efficiently direct the user through his/her way.
Detection of immovable objects on visually impaired people walking aidsTELKOMNIKA JOURNAL
One consequence of a visually impaired (blind) person is a lack of ability in the activities related to the orientation and mobility. Blind person uses a stick as a tool to know the objects that surround him/her.The objective of this research is to develop a tool for blind person which is able to recognize what object in front of him/her when he/she is walking. An attached camera will obtain an image of an object which is then processed using template matching method to identify and trace the image of the object. After getting the image of the object, furthermore calculate and compare it with the data training. The output is produced in the form of sound that in accordance with the object. The result of this research is that the best slope and distance for the template matching method to properly detect silent objects is 90 degrees and 2 meters.
Visual, navigation and communication aid for visually impaired person IJECEIAES
The loss of vision restrained the visually impaired people from performing their daily task. This issue has impeded their free-movement and turned them into dependent a person. People in this sector did not face technologies revamping their situations. With the advent of computer vision, artificial intelligence, the situation improved to a great extent. The propounded design is an implementation of a wearable device which is capable of performing a lot of features. It is employed to provide visual instinct by recognizing objects, identifying the face of choices. The device runs a pre-trained model to classify common objects from household items to automobiles items. Optical character recognition and Google translate were executed to read any text from image and convert speech of the user to text respectively. Besides, the user can search for an interesting topic by the command in the form of speech. Additionally, ultrasonic sensors were kept fixed at three positions to sense the obstacle during navigation. The display attached help in communication with deaf person and GPS and GSM module aid in tracing the user. All these features run by voice commands which are passed through the microphone of any earphone. The visual input is received through the camera and the computation task is processed in the raspberry pi board. However, the device seemed to be effective during the test and validation.
Automatic Attendance system using Facial RecognitionNikyaa7
It is a boimetric based App,which is gradually evolving in the universal boimetric solution with a virtually zero effort from the user end when compared with other boimetric options.
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1.Wireless Communication System_Wireless communication is a broad term that i...JeyaPerumal1
Wireless communication involves the transmission of information over a distance without the help of wires, cables or any other forms of electrical conductors.
Wireless communication is a broad term that incorporates all procedures and forms of connecting and communicating between two or more devices using a wireless signal through wireless communication technologies and devices.
Features of Wireless Communication
The evolution of wireless technology has brought many advancements with its effective features.
The transmitted distance can be anywhere between a few meters (for example, a television's remote control) and thousands of kilometers (for example, radio communication).
Wireless communication can be used for cellular telephony, wireless access to the internet, wireless home networking, and so on.
1.Wireless Communication System_Wireless communication is a broad term that i...
Abstract_537fbfbb4b9a70c487a6fdc8bca78d5a-2.pdf
1. FACIAL RECOGNITION SMART GLASSES FOR VISUALLY
CHALLENGED PEOPLE
Dept.of ECE
GITAM School of Technology
GITAM, Bengaluru-561203
(DEEMEDTO BE UNIVERSITY)
Student Roll. No.:
321910402019 - M.Vamsi Krishna
321910402022 - Sameeulla Khan
321910402037 - M.Vishnu Vardhan Reddy
321910402048 - R.Lavanya
Guided by:
Dr. Karthigai Pandian M
Associate Professor
Department of EECE
GITAM School of Technology
Bengaluru- 561203
2. Contents
• Abstract and Introduction
• Literature survey
• Block diagram and Methodology
• Hardware and Software
• Objectives and Applications
• References
3. Abstract:
➢ In this project, we are making a prototype of a smart eyeglass that helps visually
challenged people to recognize the person in front and also to learn about obstacles
ahead.
➢ This is enabled by Raspberry pi which is a hardware processor that takes images
from the camera and compares with the available database.
➢ If a match is found with the database, it will inform the name of person.
➢ If image is not in the database it will tell that it is an unknown person.
➢ And object detection is achieved using the ultrasonic sensor (i.e., it sends a sound
wave and sound wave is reflected back if any object is encountered).
➢ Other components involved are Pi camera, 5V battery, glasses, USB cable and
wires.
4. INTRODUCTION:
➢ People with visual impairment face various problems in their daily life as the
modern assistive devices are often not meeting the consumer requirements in term
of price and level of assistance. This project presents a new design of assistive
smart glasses for visually impaired persons.
➢ The objective is to assist in multiple daily tasks using the advantage of wearable
design format.
➢ The aim is to employ computer vision for recognition of persons and the
surrounding practiced by the blind on a daily basis.
➢ The camera is placed on the blind person's glasses. A dataset of persons gathered
from daily scenes is created to achieve the required recognition.
➢ The proposed method for the blind aims at expanding possibilities to people with
vision loss to achieve their full potential.
6. REF.
NO
Title of paper Abstract Outcome Methodology Research gap
1.
Hot Glass - Human Face,
Object And Textual
Recognition For Visually
Challenged
The design involves
human face, object
and textual
recognition which
make vision for
visually challenged.
Human Face
recognition, Object
recognition and Text
to speech conversion
Face recognition-
PCAAlgorithm.
Object Recognition-
SIR
Text Recognition-
OCR
The camera
can’t capture
360 degrees
2.
Arduino based Customized
Smart Glasses for the Blind
People
Smart aid techniques
for obstacle detection
with the fire detection
and also the
background detection.
We have developed a
low-cost solution
using the input and
output sensors
connected through
Arduino board.
Obstacle , fire and
background detection
Obstacle
detection-
Ultrasonic sensor
Fire detection –
smoke sensor
Background
detection-LDR
Object and face
recognition
7. REF.
NO
Title of paper Abstract Outcome Methodology Research gap
3.
Assistive Technology for
Integrating the Visually
Impaired in Mainstream
Education and Society
Assistive technology
tool, the system
comprises of smart
glasses, processing
unit and smart phone
application;. The
features are
developed to facilitate
VI with reading in
English and Arabic,
in-door navigation
and face recognition
Face recognition,
Reading of Arabic
and Indoor
navigation.
Face recognition-
OpenCV
Reading of
Arabic-OCR
Indoor
Navigation-
NRF24101+
module
Indoor
navigation can
be done by
image
processing
4.
Real-Time Family Member
Recognition Using
Raspberry Pi for Visually
Impaired People
This research work
firstly describes the
development and
estimation of
raspberry pi based
smart glass system to
recognize the family
members.
Identification of
family members.
Face recognition-
Image processing
Proper
identification is
not achieved
8. REF.
NO
Title of paper Abstract
Outcome
Methodology Research
gap
5.
Smart Glasses For Visually
Impaired People With Facial
Recognition
Our research describes the
design and development of
raspberry pi based smart
glasses with face recognition
and voice assistant. This idea
helps them to recognize
people around them even
when their known person is
not talking and also it has
some cool features like
playing songs, browsing etc.
Face
recognition
and hot word
detection
Face recognition-
open cv
Hot word
detection-
Porcupine
Camera could
not be
continuously
kept in On
condition.
6.
A New Method For
Recognition And Obstacle
Detection For Visually
Challenged Using Smart
Glasses Powered With
Raspberry Pi
In this paper, we are
presenting an electronic
device for obstacle detection
and face recognition to assist
visually challenged people.
The device is in the form of
smart glasses that has
ultrasonic sensor, pi camera
and raspberry pi installed on
it.
Face
recognition
Face recognition -
OpenCV
Very less
storage
9. REF.
NO
Title of paper Abstract Outcome Methodology Research
gap
7.
Smart Glasses for
Visually Impaired
Person
The paper presents a
prototype of smart glass
that can recognize and
detects object using
raspberry pi.
Obstacle detection
and
Face recognition
Face recognition-
OpenCV
Object detection-
Ultrasonic sensor
When a person
is in between
two ultrasonic
sensors, it is
not detecting
the person
8.
Motion based smart
assistant for visually
impaired people
The smart assist help
impaired people in
mobility with
confidence by
realizing the nearby
objects.
Face recognition,
exact location,
mobile
communication
Face recognition –Open
CV
Location-GPS
Mobile communication-
GSM
Size of device
is very large
10. REF
NO.
Title of paper Abstract Outcome Methodology Research gap
9.
Crosswalk Guidance
System for the Blind
Street crossing can be a
significant challenge for
visually impaired people,
limiting their mobility
especially in urban
environments. To date, there
are few solutions for this
significant problem. Current
approaches for guiding blind
pedestrians in crosswalks
have mainly focused on
detection of crosswalks and
crosswalk signals
Detecting traffic
signals and road
crossing
ROI tracker, CNN
classifier,
Proper aiming
of the camera
was difficult due
to magnified
camera settings
and lack of
visual feedback
11. Outcome of Literature Survey
The scope of the proposed project includes
1. Improving the memory to store in the database.
2. Reducing the amount of hardware components.
3. Increasing the angle and aiming of the camera.
4. Improving the accuracy of the detection of people.
12. BLOCK DIAGRAM AND METHODOLOGY
It will tell name
of the person
Images are stored
in database
Unknown
person
13. It tell the name of the
person through ear
phones when there is
matching with data set
Raspberry Pi
Pi camera capture
Ultrasonic sensor
It will tell object is
there when the
ultrasonic sensor
measures object
distance is below
threshold
16. Thonny:
IDE stands for Integrated Development Environment. It's a coding tool
which allows us to write, test, and debug our code in an easier way, as
they typically offer code completion or code insight by highlighting,
resource management, debugging tools,…etc.
SOFTWARE USED
17. Work carried out so far and Result
• We are working on the assembling the components as per the requirements.
• We have worked on the hardware components to understand how to
measure distance using ultrasonic sensor and capturing of images using Pi
cam.
18. REFERENCES:
1. Diwakar Srinath A", Praveen Ram A.R2, Siva R", Kalaiselvi V.K.G", Ajitha G “Hot Glass - Human Face, Object And
Textual Recognition for Visually Challenged” - 2017 Second International Conference On Computing and
Communications Technologies(ICCCT 17).
2. Mohammed Noman, Wessam Shehieb & Tazeen Sharif “Assistive Technology for Integrating the Visually Impaired in
Mainstream Education and Societ” -2019 Advances in Science and Engineering Technology International Conferences
(ASET).
3. Sanjay Kumar Y R, Nivethetha T, Priyadharshini P ” Smart Glasses For Visually Impaired People With Facial
Recognition”- 2022 International Conference on Communication, Computing and Internet of Things (IC3IoT).
4. Md. Tobibul Islam, Mohiuddin Ahmad, Akash Shingha Bappy “Real-Time Family Member Recognition Using
Raspberry Pi for Visually Impaired People”- 2020 IEEE Region 10 Symposium (TENSYMP), 5-7 June 2020, Dhaka,
Bangladesh.
5. Prathima Samuda , Praveena N G , Nithiya C “Arduino based Customized Smart Glasses for the Blind People” -
Proceedings of the Second International Conference on Artificial Intelligence and Smart Energy (ICAIS-2022) IEEE
Xplore Part Number: CFP22OAB-ART; ISBN: 978-1-6654-0052-7 .
6. K. Sundar Srinivas, K. Sahithya, G. Lakshmi Tejaswi, K. Hari Gopal, B. Pavan Karthik “A New Method For
Recognition And Obstacle Detection For Visually Challenged Using Smart Glasses Powered With Raspberry Pi”-
International Journal of Engineering Applied Sciences and Technology, 2020 Vol. 5, Issue 1, ISSN No. 2455-2143,
Pages 408-412 Published Online May 2020.