Many visually impaired people worldwide are unable to travel safely and autonomously because they are physically unable to perceive effective visual information during their daily lives. In this research, we study how to extract the character information of the road sign and transmit it to the visually impaired effectively, so they can understand easier. Experimental method is to apply the Maximally Stable External Region and Stroke Width Transform method in Phase I so that the visually impaired person can recognize the letters on the road signs. It is to convey text information to the disabled. The result of Phase I using samples of simple road signs was to extract the sign information after dividing the exact character area, but the accuracy was not good for the Hangul (Korean characters) information. The initial experimental results in the Phase II succeeded in transmitting the text information on Phase I to the visually impaired. In the future, it will be required to develop a wearable character recognition system that can be attached to the visually impaired. In order to perform this task, we need to develop and verify a miniaturized and wearable character recognition system. In this paper, we examined the method of recognizing road sign characters on the road and presented a possibility that may be applicable to our final development.
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.
IRJET- Indoor Shopping System for Visually Impaired PeopleIRJET Journal
The document describes a proposed indoor shopping system to help visually impaired people shop independently. The system uses technologies like optical character recognition, text-to-speech, RFID, and ultrasonic sensors integrated with a Raspberry Pi. OCR is used to identify products from images and text-to-speech converts the output to audio. RFID tags on products and sections provide identification and location information to users via a reader. Ultrasonic sensors detect obstacles and alert users with a buzzer to avoid collisions while shopping. The system aims to address difficulties visually impaired people face during independent indoor shopping.
Application for Iraqi sign language translation on Android system IJECEIAES
Deaf people suffer from difficulty in social communication, especially those who have been denied the blessing of hearing before the acquisition of spoken language and before learning to read and write. For the purpose of employing mobile devices for the benefit of these people, their teachers and everyone who has contact with them, this research aims to design an application for social communication and learning by translating Iraqi sign language into text in Arabic and vice versa. Iraqi sign language has been chosen because of a lack of applications for this field. The current research, to the best of our knowledge, is the first of its kind in Iraq. The application is open source; words that are not found in the application database can be processed by translating them into letters alphabetically. The importance of the application lies in the fact that it is a means of communication and e-learning through Iraqi sign language, reading and writing in Arabic. Similarly, it is regarded as a means of social communication between deaf people and those with normal hearing. This application is designed by using JAVA language and it was tested on several deaf students at Al-Amal Institute for Special Needs Care in Mosul, Iraq. It was well comprehended and accepted.
IRJET- Gesture Drawing Android Application for Visually-Impaired PeopleIRJET Journal
The document describes a proposed Android application to help visually impaired people make phone calls and send messages with their current location independently. The application uses gesture drawing, haptic feedback, and audio feedback to allow users to store contacts along with assigned gestures and then make calls or send messages by drawing the gestures. When gestures are drawn correctly, haptic and audio feedback are provided to confirm the action to the user. The proposed application aims to provide an easier alternative to searching contact lists manually and does not require visual feedback.
A Model for Car Plate Recognition & Speed Tracking (CPR-STS) using Machine Le...CSCJournals
The transportation challenges experienced in major cities as a result of influx of people in search of greener pastures is increasing on a daily basis. This results in an increase in the number of cars plying and competing for driving space on narrow roads. Many drivers violate traffic laws as a result of this and how to prosecute them without chasing them remains an issue to be addressed. Therefore, this research presents a model that can be used to solve this challenge using machine learning algorithms. The model consists of recognition modules such as image acquisition, Gaussian blur, localization of car plate, character segmentation and optical character recognition of car plate. K-NN Algorithm was used for training licensed plate font type spanning A-Z and 0-9 while the speed tracking module used a camera which is automatically self-initiated to track the speed of any moving object within its range of focus. The performance of the model was evaluated using metrics such as recognition accuracy, positive prediction value, negative prediction value, specificity and sensitivity. A tracking accuracy of 82% was achieved.
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.
The aim of this paper is to help the blind people to identify and catch the public transport vehicles with the help of Light Fidelity technology. It is a Navigation aid. When the bus arrives at the bus stand, transmitter in the bus transmits the light signals and receiver in the stick, receives the light signals and a sound signal is generated through the speaker present in the stick. The sound message contains the bus number and the destination of the bus. In addition to this, if the person is absconded or lost, details of the location will be sent to his/her family members by pressing a button. This is made possible with the help of Global System for Mobile (GSM). Finally, presence of water can be detected along the blind person’s path, with the help of water sensors.
Smart Card: A study of new invention on bus fare in Dhaka cityMd. Abdul Munem
Technology is developing day to day. So we have to be familiar with technology. Digital payment system
is one of them. Our government will launch a pilot project for transportation under 22 buses on 42 routes.
It will be better if the smart card will included in that project. In the term paper I have focused the problems
we faced on public transport.
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.
IRJET- Indoor Shopping System for Visually Impaired PeopleIRJET Journal
The document describes a proposed indoor shopping system to help visually impaired people shop independently. The system uses technologies like optical character recognition, text-to-speech, RFID, and ultrasonic sensors integrated with a Raspberry Pi. OCR is used to identify products from images and text-to-speech converts the output to audio. RFID tags on products and sections provide identification and location information to users via a reader. Ultrasonic sensors detect obstacles and alert users with a buzzer to avoid collisions while shopping. The system aims to address difficulties visually impaired people face during independent indoor shopping.
Application for Iraqi sign language translation on Android system IJECEIAES
Deaf people suffer from difficulty in social communication, especially those who have been denied the blessing of hearing before the acquisition of spoken language and before learning to read and write. For the purpose of employing mobile devices for the benefit of these people, their teachers and everyone who has contact with them, this research aims to design an application for social communication and learning by translating Iraqi sign language into text in Arabic and vice versa. Iraqi sign language has been chosen because of a lack of applications for this field. The current research, to the best of our knowledge, is the first of its kind in Iraq. The application is open source; words that are not found in the application database can be processed by translating them into letters alphabetically. The importance of the application lies in the fact that it is a means of communication and e-learning through Iraqi sign language, reading and writing in Arabic. Similarly, it is regarded as a means of social communication between deaf people and those with normal hearing. This application is designed by using JAVA language and it was tested on several deaf students at Al-Amal Institute for Special Needs Care in Mosul, Iraq. It was well comprehended and accepted.
IRJET- Gesture Drawing Android Application for Visually-Impaired PeopleIRJET Journal
The document describes a proposed Android application to help visually impaired people make phone calls and send messages with their current location independently. The application uses gesture drawing, haptic feedback, and audio feedback to allow users to store contacts along with assigned gestures and then make calls or send messages by drawing the gestures. When gestures are drawn correctly, haptic and audio feedback are provided to confirm the action to the user. The proposed application aims to provide an easier alternative to searching contact lists manually and does not require visual feedback.
A Model for Car Plate Recognition & Speed Tracking (CPR-STS) using Machine Le...CSCJournals
The transportation challenges experienced in major cities as a result of influx of people in search of greener pastures is increasing on a daily basis. This results in an increase in the number of cars plying and competing for driving space on narrow roads. Many drivers violate traffic laws as a result of this and how to prosecute them without chasing them remains an issue to be addressed. Therefore, this research presents a model that can be used to solve this challenge using machine learning algorithms. The model consists of recognition modules such as image acquisition, Gaussian blur, localization of car plate, character segmentation and optical character recognition of car plate. K-NN Algorithm was used for training licensed plate font type spanning A-Z and 0-9 while the speed tracking module used a camera which is automatically self-initiated to track the speed of any moving object within its range of focus. The performance of the model was evaluated using metrics such as recognition accuracy, positive prediction value, negative prediction value, specificity and sensitivity. A tracking accuracy of 82% was achieved.
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.
The aim of this paper is to help the blind people to identify and catch the public transport vehicles with the help of Light Fidelity technology. It is a Navigation aid. When the bus arrives at the bus stand, transmitter in the bus transmits the light signals and receiver in the stick, receives the light signals and a sound signal is generated through the speaker present in the stick. The sound message contains the bus number and the destination of the bus. In addition to this, if the person is absconded or lost, details of the location will be sent to his/her family members by pressing a button. This is made possible with the help of Global System for Mobile (GSM). Finally, presence of water can be detected along the blind person’s path, with the help of water sensors.
Smart Card: A study of new invention on bus fare in Dhaka cityMd. Abdul Munem
Technology is developing day to day. So we have to be familiar with technology. Digital payment system
is one of them. Our government will launch a pilot project for transportation under 22 buses on 42 routes.
It will be better if the smart card will included in that project. In the term paper I have focused the problems
we faced on public transport.
This document presents a device called FOR(E)SIGHT that was designed to assist visually impaired people. FOR(E)SIGHT uses computer vision techniques like OpenCV, optical character recognition and text-to-speech to help blind users identify objects, read text, and understand gestures. It consists of a Raspberry Pi microcontroller, camera, ultrasonic sensor and headphones. The device detects objects and text using the camera, extracts text using OCR, and converts it to audio using text-to-speech synthesis which is played through headphones. The goal was to create an affordable, small and easy to use device to help blind people with daily living activities.
CONTEXT-BASED BARRIER NOTIFICATION SERVICE TOWARD OUTDOOR SUPPORT FOR THE ELD...ijcsit
This document summarizes a proposed context-based mobile service that notifies elderly users of barriers in outdoor environments. The service collects barrier information through user participation and filters notifications based on individual user contexts. An experiment was conducted in Tokyo to test the usability and accuracy of the information filtering. Notifications are provided to users via mobile phones equipped with GPS when they are near registered barriers or useful information. The goal is to promote social participation by lowering anxiety for elderly users when outdoors.
IRJET- Review on Raspberry Pi based Assistive Communication System for Blind,...IRJET Journal
This document summarizes a research paper that aims to develop an assistive communication device for blind, deaf, and dumb people. The device uses image processing and optical character recognition to convert text images into voice for blind users. It interprets sign language movements with video and converts them to text for deaf users. The device also has GPS tracking and ultrasonic sensors to help users who are in trouble or detect obstacles. The researchers aim to integrate these features on a single low-cost device using a Raspberry Pi microcontroller to help disabled people communicate more easily.
Smartcard based Android Application for Public Transport Ticketing SystemNeelam Gulrajani
This document summarizes a research paper that proposes a smartcard-based Android application for public transport ticketing in India. The application aims to improve the user experience of ticketing by applying principles of user-centered design and usability. It allows users to select departure and destination locations on an interactive map, purchase tickets, and view travel details. The application was designed and tested on Android devices. Future work could expand the system to integrate with GPS and support multiple mobile platforms and languages.
Face recognition smart cane using haar-like features and eigenfacesTELKOMNIKA JOURNAL
1) The document describes a prototype for a smart cane with face recognition capabilities to help visually impaired people identify faces.
2) The prototype uses a Raspberry Pi, camera mounted on eyeglasses, and earphones to provide audio feedback. The camera captures images that are analyzed using Haar-like features and eigenfaces algorithms for face detection and recognition.
3) Testing showed the prototype could recognize faces within 1-1.5 meters with 91.67% accuracy for frontal faces but only 18-32% for other positions. It took around 3 seconds to recognize one face and longer for multiple faces.
Traffic accidents are one of the leading causes of fatalities in the world. An important indicator of survival rates after an accident is the time between the accident and when emergency medical personnel are dispatched to the scene. Eliminating the time between when an accident occurs and when first responders are dispatched to the scene decreases mortality rates by 6%.. By combining smart phones with existing vehicles through an appropriate interface we are able to move closer to the smart vehicle paradigm, offering the user new functionalities and services when driving. In this application we propose an Android based application that monitors the vehicle through an On Board Diagnostics (OBD-II) interface, being able to detect accidents. The application reacts to positive detection by sending details about the accident through SMS to pre-defined destinations, immediately followed by an automatic phone call to the emergency services.
This document describes a project aimed at developing an assistive device to help blind people shop independently in supermarkets. The device would use computer vision and object detection algorithms to identify products and provide information to users through audio or other feedback. The system would include a camera and sensors integrated into a portable hardware device. It discusses the challenges blind people face in tasks like identifying products without assistance. The goal is to advance assistive technologies that improve quality of life and independence for visually impaired individuals.
IRJET- Design and Development of Tesseract-OCR Based Assistive System to Conv...IRJET Journal
The document describes the design and development of an assistive system using Tesseract optical character recognition (OCR) and a Raspberry Pi to convert captured text into voice output for visually impaired users. A Raspberry Pi with a webcam or mobile camera is used to focus on and capture printed text. The text is processed using OCR and segmentation before feature extraction and character recognition with Tesseract. Recognized text characters are converted to audio format using Festival so they can be accessed by blind users. An ultrasonic sensor is also included to allow users to determine the type of object, such as a menu, being interacted with. The system aims to provide faster reading access compared to braille.
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.
Communication among blind, deaf and dumb PeopleIJAEMSJORNAL
Now-a-days Science and Technology have made the human world so easy but still some physically and visually challenged people suffer from communication with others. In this project, we are going to propose a new system prototype called communication among Blind, deaf and dumb people .This will helps the disabled people to overcome their difficulties in communicating with some other people with disabilities or normal people. The blind people will communicate through the speakers, the deaf and dumb people will see through it and reply through typing in a terminal .These are all done as an application , so that will be easily understand by the people with disabilities.
This document describes a proposed Android application called SHRAVAN that would allow visually impaired users to send and receive text messages. The application would use text-to-speech to read incoming messages aloud and a Braille interface for composing responses. Users would navigate the application through gestures and sensors, avoiding the need for expensive specialized hardware. The goal is to provide an affordable way for blind smartphone users to communicate via SMS using interfaces they are already familiar with.
SMARCOS Abstract Paper submitted to ICCHP 2012Smarcos Eu
This study is part of the European project "Smarcos" (http://www.smarcos-project.eu/) that includes among its goals the development of services which are specifically designed and accessible for blind users.
In this paper we present the prototype application designed to make the main phone features available in a way which is accessible for a blind user. The prototype has been developed to firstly evaluate the interaction modalities based on gestures, audio and vibro-tactile feedback.
Smart Voting System with Face RecognitionNikhil Katte
This document proposes a smart voting system using face recognition to allow people to vote digitally using their smartphones. The system would have a server, registration center application, and voter android application. It works by capturing a live image of the voter's face on their phone, sending it to the server for authentication using face recognition algorithms, and allowing them to vote if authorized. The system aims to modernize voting and make it more convenient using digital technologies while maintaining security.
IRJET- Voice Assistant for Visually Impaired PeopleIRJET Journal
The document proposes developing a voice assistant application for Android to help visually impaired people perform daily tasks using their smartphones. The application would allow users to check messages, calls, take notes, use optical character recognition to read text images, get navigation assistance, and browse the web using text-to-speech and speech recognition. The application aims to make smartphones more accessible and useful for people with visual impairments.
IRJET - Sign Language Text to Speech Converter using Image Processing and...IRJET Journal
This document describes a sign language text-to-speech converter system using image processing and convolutional neural networks (CNNs). The system captures images of hand gestures using a camera, applies image processing techniques like thresholding and blurring, and then uses a CNN model trained on a dataset of gestures to recognize the gestures and convert them to text and speech. The system was able to accurately recognize gestures for letters and numbers with about 85% accuracy. Future work may involve expanding the dataset to include more signs and working towards word and sentence recognition.
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 Recognition and Door Opening Assistant for Visually ImpairedUllas Puntambekar
Visually impaired people face immense amount of problems in their daily lives. We usually see in media demonstrations of help, people helping blind people, such scenarios very well explain the degree of difficulty that visually impaired people face in their daily lives. Even when living alone at their home they cannot feel safe with the exponential rate of crime. With the help of face recognition and use of smart phones we tried to eliminate this problem.
IRJET - Expiry Date and Cost Tracking in Medicine for Visually ImpairedIRJET Journal
This document describes a proposed system to help visually impaired people identify expiry dates and prices on medicine packages. The system would use a camera attached to a microcontroller to capture images of medicine labels. Optical character recognition (Tesseract) would then be used to extract the expiry date and price text. Contour analysis would help locate this relevant information. If the medicine's expiry date indicates it is still consumable, a voice output would inform the user. The system aims to allow visually impaired people to independently determine expiry dates and costs without relying on others. It discusses challenges with current text recognition approaches and the need for alternative methods to reliably identify expiry dates. A flow diagram is also provided outlining the key steps of the proposed system
IRJET- Development of a Face Recognition System with Deep Learning and Py...IRJET Journal
This document presents the development of a face recognition system using deep learning algorithms and PyTorch. The system was trained on a dataset of 94 face images and was able to extract relevant facial features to encode faces and recognize them with 95% accuracy. The system represents faces as 128-dimensional embeddings that allow for efficient comparison of faces within the dataset. It can recognize faces in the dataset and continuously learn by incorporating new face images to improve its predictions.
Survey on Human Computer interaction for disabled persons Muhammad Bilal
This document presents a survey of 10 different techniques for facilitating human-computer interaction for disabled persons. The techniques analyzed include nose tracking cursor control, facial recognition, electrooculography (EOG), vocal mouse control using speech recognition, eye movement detection, hand gesture recognition, tongue control systems, foot mouse control using pressure sensors, finger gesture recognition using color markers, and control using nose tracking and face detection. The techniques are compared based on parameters like efficiency, accuracy, sensors used, cost, whether they include facial recognition, gesture recognition, eye-blink detection or speech detection. The survey concludes that techniques using only cameras are low-cost and easy to use while being non-intrusive, and that outdoor-compatible systems
An Assistive System for Visually Impaired PeopleIRJET Journal
This document describes a proposed assistive system for visually impaired people that uses computer vision and machine learning techniques. The system is designed to help visually impaired individuals navigate indoor and outdoor environments independently. It uses a Python-based program with OpenCV and YOLO object detection to identify objects and text in images captured by a camera. Text detected in images is converted to audio using Tesseract OCR and a text-to-speech engine to allow users to hear identified objects and text. The system aims to provide navigation assistance and read text aloud to help visually impaired people live more independently.
IRJET- Navigation and Camera Reading System for Visually ImpairedIRJET Journal
This document describes a proposed navigation and camera reading system to help visually impaired people. It uses computer vision techniques like object detection and depth perception to navigate without collisions and detect different object types and distances. It also implements a navigation feature to guide the user to their destination based on their input. The system aims to provide multi-feature, high accuracy navigation assistance by processing images and using digital image processing techniques. It analyzes images to identify objects, compute distances and directions to navigate and read text using optical character recognition and text-to-speech synthesis.
This document presents a device called FOR(E)SIGHT that was designed to assist visually impaired people. FOR(E)SIGHT uses computer vision techniques like OpenCV, optical character recognition and text-to-speech to help blind users identify objects, read text, and understand gestures. It consists of a Raspberry Pi microcontroller, camera, ultrasonic sensor and headphones. The device detects objects and text using the camera, extracts text using OCR, and converts it to audio using text-to-speech synthesis which is played through headphones. The goal was to create an affordable, small and easy to use device to help blind people with daily living activities.
CONTEXT-BASED BARRIER NOTIFICATION SERVICE TOWARD OUTDOOR SUPPORT FOR THE ELD...ijcsit
This document summarizes a proposed context-based mobile service that notifies elderly users of barriers in outdoor environments. The service collects barrier information through user participation and filters notifications based on individual user contexts. An experiment was conducted in Tokyo to test the usability and accuracy of the information filtering. Notifications are provided to users via mobile phones equipped with GPS when they are near registered barriers or useful information. The goal is to promote social participation by lowering anxiety for elderly users when outdoors.
IRJET- Review on Raspberry Pi based Assistive Communication System for Blind,...IRJET Journal
This document summarizes a research paper that aims to develop an assistive communication device for blind, deaf, and dumb people. The device uses image processing and optical character recognition to convert text images into voice for blind users. It interprets sign language movements with video and converts them to text for deaf users. The device also has GPS tracking and ultrasonic sensors to help users who are in trouble or detect obstacles. The researchers aim to integrate these features on a single low-cost device using a Raspberry Pi microcontroller to help disabled people communicate more easily.
Smartcard based Android Application for Public Transport Ticketing SystemNeelam Gulrajani
This document summarizes a research paper that proposes a smartcard-based Android application for public transport ticketing in India. The application aims to improve the user experience of ticketing by applying principles of user-centered design and usability. It allows users to select departure and destination locations on an interactive map, purchase tickets, and view travel details. The application was designed and tested on Android devices. Future work could expand the system to integrate with GPS and support multiple mobile platforms and languages.
Face recognition smart cane using haar-like features and eigenfacesTELKOMNIKA JOURNAL
1) The document describes a prototype for a smart cane with face recognition capabilities to help visually impaired people identify faces.
2) The prototype uses a Raspberry Pi, camera mounted on eyeglasses, and earphones to provide audio feedback. The camera captures images that are analyzed using Haar-like features and eigenfaces algorithms for face detection and recognition.
3) Testing showed the prototype could recognize faces within 1-1.5 meters with 91.67% accuracy for frontal faces but only 18-32% for other positions. It took around 3 seconds to recognize one face and longer for multiple faces.
Traffic accidents are one of the leading causes of fatalities in the world. An important indicator of survival rates after an accident is the time between the accident and when emergency medical personnel are dispatched to the scene. Eliminating the time between when an accident occurs and when first responders are dispatched to the scene decreases mortality rates by 6%.. By combining smart phones with existing vehicles through an appropriate interface we are able to move closer to the smart vehicle paradigm, offering the user new functionalities and services when driving. In this application we propose an Android based application that monitors the vehicle through an On Board Diagnostics (OBD-II) interface, being able to detect accidents. The application reacts to positive detection by sending details about the accident through SMS to pre-defined destinations, immediately followed by an automatic phone call to the emergency services.
This document describes a project aimed at developing an assistive device to help blind people shop independently in supermarkets. The device would use computer vision and object detection algorithms to identify products and provide information to users through audio or other feedback. The system would include a camera and sensors integrated into a portable hardware device. It discusses the challenges blind people face in tasks like identifying products without assistance. The goal is to advance assistive technologies that improve quality of life and independence for visually impaired individuals.
IRJET- Design and Development of Tesseract-OCR Based Assistive System to Conv...IRJET Journal
The document describes the design and development of an assistive system using Tesseract optical character recognition (OCR) and a Raspberry Pi to convert captured text into voice output for visually impaired users. A Raspberry Pi with a webcam or mobile camera is used to focus on and capture printed text. The text is processed using OCR and segmentation before feature extraction and character recognition with Tesseract. Recognized text characters are converted to audio format using Festival so they can be accessed by blind users. An ultrasonic sensor is also included to allow users to determine the type of object, such as a menu, being interacted with. The system aims to provide faster reading access compared to braille.
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.
Communication among blind, deaf and dumb PeopleIJAEMSJORNAL
Now-a-days Science and Technology have made the human world so easy but still some physically and visually challenged people suffer from communication with others. In this project, we are going to propose a new system prototype called communication among Blind, deaf and dumb people .This will helps the disabled people to overcome their difficulties in communicating with some other people with disabilities or normal people. The blind people will communicate through the speakers, the deaf and dumb people will see through it and reply through typing in a terminal .These are all done as an application , so that will be easily understand by the people with disabilities.
This document describes a proposed Android application called SHRAVAN that would allow visually impaired users to send and receive text messages. The application would use text-to-speech to read incoming messages aloud and a Braille interface for composing responses. Users would navigate the application through gestures and sensors, avoiding the need for expensive specialized hardware. The goal is to provide an affordable way for blind smartphone users to communicate via SMS using interfaces they are already familiar with.
SMARCOS Abstract Paper submitted to ICCHP 2012Smarcos Eu
This study is part of the European project "Smarcos" (http://www.smarcos-project.eu/) that includes among its goals the development of services which are specifically designed and accessible for blind users.
In this paper we present the prototype application designed to make the main phone features available in a way which is accessible for a blind user. The prototype has been developed to firstly evaluate the interaction modalities based on gestures, audio and vibro-tactile feedback.
Smart Voting System with Face RecognitionNikhil Katte
This document proposes a smart voting system using face recognition to allow people to vote digitally using their smartphones. The system would have a server, registration center application, and voter android application. It works by capturing a live image of the voter's face on their phone, sending it to the server for authentication using face recognition algorithms, and allowing them to vote if authorized. The system aims to modernize voting and make it more convenient using digital technologies while maintaining security.
IRJET- Voice Assistant for Visually Impaired PeopleIRJET Journal
The document proposes developing a voice assistant application for Android to help visually impaired people perform daily tasks using their smartphones. The application would allow users to check messages, calls, take notes, use optical character recognition to read text images, get navigation assistance, and browse the web using text-to-speech and speech recognition. The application aims to make smartphones more accessible and useful for people with visual impairments.
IRJET - Sign Language Text to Speech Converter using Image Processing and...IRJET Journal
This document describes a sign language text-to-speech converter system using image processing and convolutional neural networks (CNNs). The system captures images of hand gestures using a camera, applies image processing techniques like thresholding and blurring, and then uses a CNN model trained on a dataset of gestures to recognize the gestures and convert them to text and speech. The system was able to accurately recognize gestures for letters and numbers with about 85% accuracy. Future work may involve expanding the dataset to include more signs and working towards word and sentence recognition.
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 Recognition and Door Opening Assistant for Visually ImpairedUllas Puntambekar
Visually impaired people face immense amount of problems in their daily lives. We usually see in media demonstrations of help, people helping blind people, such scenarios very well explain the degree of difficulty that visually impaired people face in their daily lives. Even when living alone at their home they cannot feel safe with the exponential rate of crime. With the help of face recognition and use of smart phones we tried to eliminate this problem.
IRJET - Expiry Date and Cost Tracking in Medicine for Visually ImpairedIRJET Journal
This document describes a proposed system to help visually impaired people identify expiry dates and prices on medicine packages. The system would use a camera attached to a microcontroller to capture images of medicine labels. Optical character recognition (Tesseract) would then be used to extract the expiry date and price text. Contour analysis would help locate this relevant information. If the medicine's expiry date indicates it is still consumable, a voice output would inform the user. The system aims to allow visually impaired people to independently determine expiry dates and costs without relying on others. It discusses challenges with current text recognition approaches and the need for alternative methods to reliably identify expiry dates. A flow diagram is also provided outlining the key steps of the proposed system
IRJET- Development of a Face Recognition System with Deep Learning and Py...IRJET Journal
This document presents the development of a face recognition system using deep learning algorithms and PyTorch. The system was trained on a dataset of 94 face images and was able to extract relevant facial features to encode faces and recognize them with 95% accuracy. The system represents faces as 128-dimensional embeddings that allow for efficient comparison of faces within the dataset. It can recognize faces in the dataset and continuously learn by incorporating new face images to improve its predictions.
Survey on Human Computer interaction for disabled persons Muhammad Bilal
This document presents a survey of 10 different techniques for facilitating human-computer interaction for disabled persons. The techniques analyzed include nose tracking cursor control, facial recognition, electrooculography (EOG), vocal mouse control using speech recognition, eye movement detection, hand gesture recognition, tongue control systems, foot mouse control using pressure sensors, finger gesture recognition using color markers, and control using nose tracking and face detection. The techniques are compared based on parameters like efficiency, accuracy, sensors used, cost, whether they include facial recognition, gesture recognition, eye-blink detection or speech detection. The survey concludes that techniques using only cameras are low-cost and easy to use while being non-intrusive, and that outdoor-compatible systems
An Assistive System for Visually Impaired PeopleIRJET Journal
This document describes a proposed assistive system for visually impaired people that uses computer vision and machine learning techniques. The system is designed to help visually impaired individuals navigate indoor and outdoor environments independently. It uses a Python-based program with OpenCV and YOLO object detection to identify objects and text in images captured by a camera. Text detected in images is converted to audio using Tesseract OCR and a text-to-speech engine to allow users to hear identified objects and text. The system aims to provide navigation assistance and read text aloud to help visually impaired people live more independently.
IRJET- Navigation and Camera Reading System for Visually ImpairedIRJET Journal
This document describes a proposed navigation and camera reading system to help visually impaired people. It uses computer vision techniques like object detection and depth perception to navigate without collisions and detect different object types and distances. It also implements a navigation feature to guide the user to their destination based on their input. The system aims to provide multi-feature, high accuracy navigation assistance by processing images and using digital image processing techniques. It analyzes images to identify objects, compute distances and directions to navigate and read text using optical character recognition and text-to-speech synthesis.
Forey: An Android Application for the Visually ImpairedIRJET Journal
The document describes an Android application called Forey that is designed to help visually impaired people with daily tasks. The application has three main features: currency detection using machine learning to identify banknotes through photos, QR code scanning to identify objects, and an audio stories library to allow users to connect. The application is intended to give visually impaired users more independence by allowing them to identify currency, objects, and share experiences without needing assistance from others.
Eye-Blink Detection System for Virtual KeyboardIRJET Journal
This document describes an eye-blink detection system that can be used as a virtual keyboard. It detects eye blinks using a webcam and facial recognition software. When each letter on the virtual keyboard is highlighted, the user can select it by blinking for one second. This allows people with physical disabilities to type and interact with computers using only their eyes. The system was tested and users were able to type words at a rate of 13-15 words per minute. Overall, the eye-blink detection system aims to enhance accessibility and independence for disabled users.
Visual Product Identification For Blind PeoplesIRJET Journal
1) The document presents a prototype system to assist blind people in reading printed text on handheld objects. It uses a camera, data processing, and audio output.
2) A motion-based method is used to isolate the object of interest from other objects in the camera view. Text localization and recognition algorithms are then used to extract and identify text from the isolated region.
3) The system is evaluated on its ability to localize and recognize text from images of objects with complex backgrounds, and on its usability with blind users. Future work will focus on improving text localization and the user interface.
This document presents a study on sign language recognition using computer vision techniques. It aims to develop a system that can identify characters and numbers in Indian Sign Language (ISL) using convolutional neural networks. ISL uses both hands to communicate unlike American Sign Language which uses a single hand. The system creates a dataset of ISL gestures and trains a CNN model on it. It then tests the ability of the trained model to accurately predict numbers from 1 to 10 and letters from A to Z when presented with new sign language inputs. The model achieves over 90% accuracy on test data, providing an effective way to translate ISL signs and bridge communication between deaf/mute and non-signing individuals.
Text Detection and Recognition with Speech Output for Visually Challenged Per...IJERA Editor
The document reviews existing systems that aim to assist visually impaired persons by detecting and recognizing text from images and converting it to speech. It discusses how optical character recognition and text-to-speech technologies have been used to develop applications like newspaper reading systems, signage recognition systems, and camera-based text reading systems. The document also summarizes various text detection and recognition methods that have been used, such as gradient feature-based, color segmentation-based, texture feature-based, and layout analysis-based approaches.
The document describes a proposed system called SRAVIP (Smart Robot Assistant for Visually Impaired Persons) that aims to assist visually impaired individuals in navigating indoor environments. SRAVIP includes two subsystems: 1) an initialization system to create an environment map and register users, and 2) a real-time operation system to navigate the mobile robot and communicate with users through speech or text. The robot utilizes sensors and simultaneous localization and mapping to safely guide a registered user to their desired location indoors. The system was tested successfully using a Turtlebot3 robot at a university campus.
Product Label Reading System for visually challenged peopleIRJET Journal
1) The document proposes a camera-based assistive text reading system to help blind people read text labels on handheld objects. It uses computer vision techniques like stroke width transform to isolate the object of interest and detect the region of interest.
2) In the region of interest, the system performs text localization using gradient features and edge distributions. It then recognizes text using optical character recognition and outputs it verbally for the user.
3) The system aims to achieve robust text extraction and recognition from complex backgrounds while focusing on usability. It analyzes existing assistive technologies and proposes an improved workflow including image capture, processing, and audio output.
Sign Language Recognition using MediapipeIRJET Journal
This document summarizes a student research project that aims to develop a sign language recognition system using the Mediapipe framework. The system takes video input of signed letters from the American Sign Language alphabet and outputs the recognized letters in text format. The document provides background on sign language and gesture recognition, describes the Mediapipe framework and implementation methodology using KNN classification, and presents preliminary results of the system detecting hand positions and recognizing letters in real-time. The overall goal is to reduce communication barriers for deaf individuals by translating sign language to written text.
F2R Analyzer Using Machine Learning and Deep LearningIRJET Journal
This document discusses facial emotion recognition (FER) and optical character recognition (OCR). It describes the processes involved in FER, including face detection, feature extraction, and expression classification. It also outlines the steps in OCR, such as image acquisition, pre-processing, character segmentation, feature extraction, classification, and post-processing. The document examines related work in FER and OCR and discusses implementations and applications. It explores using FER to analyze user experiences and profiles and the potential risks of inaccurate profiling.
IRJET - Smart E – Cane for the Visually Challenged and Blind using ML Con...IRJET Journal
This document proposes a smart cane called the Smart E-Cane for visually impaired and blind people using machine learning concepts. The Smart E-Cane will include sensors for obstacle detection and provide location-based feedback. It will also be able to detect different raised surfaces like stairs, slopes, or rocks using a magnetometer and machine learning models trained on sensor data. This will help identify obstacles more precisely. An accompanying wearable band is also proposed to locate the cane if misplaced and send the user's location via IoT in emergencies. The system aims to provide independence and safety for visually impaired users while walking without assistance.
IRJET- Persons Identification Tool for Visually Impaired - Digital EyeIRJET Journal
This document presents a face detection and recognition system to help visually impaired people identify individuals. The system uses computer vision techniques like convolutional neural networks and cascade classifiers for face detection with high accuracy. It then performs face recognition on pre-trained image datasets to determine a person's identity, as well as their emotion, age and gender. The system was tested on a combined dataset of images and achieved 95.7% accuracy in identifying faces, even when there were many faces present. This person identification tool aims to help the visually impaired better interact with others by audibly providing the name and attributes of detected individuals.
IRJET- Review on Text Recognization of Product for Blind Person using MATLABIRJET Journal
This document summarizes a research paper that proposes a system to help blind people read text on product labels and documents using a camera and MATLAB software. The system uses image processing techniques like converting images to grayscale, binarization, and filtering to isolate text from complex backgrounds. It then applies optical character recognition to identify the text and provide information to blind users. The proposed system aims to address limitations of prior methods that struggled with non-horizontal text, complex backgrounds, and positioning objects in the camera view. It extracts a region of interest around a product using motion detection and recognizes text regardless of orientation.
IRJET- Hand Gesture Recognition System using Convolutional Neural NetworksIRJET Journal
The document presents a hand gesture recognition system using convolutional neural networks. The system aims to enable communication between deaf or mute individuals and those who do not understand sign language. It works by capturing an image of a hand gesture via camera, extracting features from the image, detecting the sign using a CNN model, and converting the sign to text or speech. The system can also convert text or speech to the corresponding sign. The CNN model achieves an accuracy of 95.6% for sign recognition, outperforming previous methods. A real-time prototype allows signing and two-way communication between individuals on different devices.
IRJET-Human Face Detection and Identification using Deep Metric LearningIRJET Journal
This document discusses a project that uses deep metric learning techniques for human face detection and identification in images and videos. Deep metric learning outputs a real-valued vector rather than a single classification. It uses libraries like OpenCV, Dlib, scikit-learn and Keras to build neural networks for facial recognition. The goals are to develop a system that can identify faces even from low quality images with variations in illumination, expression, angle and occlusions. Existing face recognition has challenges in these conditions, so the aim is to improve accuracy rates for normal and non-ideal images through deep metric learning approaches.
IRJET- A Smart Personal AI Assistant for Visually Impaired People: A SurveyIRJET Journal
This document summarizes a research paper that surveys potential solutions for developing a smart personal AI assistant to help visually impaired people. It discusses using technologies like artificial intelligence, voice recognition, image recognition and text recognition through an Android application. The application could assist users by recognizing surroundings using images, responding to voice commands, and providing text recognition to read text aloud. The paper reviews related works that used technologies like object detection, neural networks and Google's Vision and Dialogflow APIs. It proposes an application with modules for image recognition, speech recognition, interaction with a chatbot, and text recognition to help visually impaired people interact with their environment and carry out daily tasks.
IRJET- VI Spectacle – A Visual Aid for the Visually ImpairedIRJET Journal
This document describes a device called VI Spectacle that aims to help visually impaired people navigate their surroundings safely and independently. The device consists of an ESP32 camera, ultrasonic sensors, and a mobile application. The camera streams video in real-time to the mobile app. Using object detection algorithms, the app analyzes the video to identify obstacles. It then alerts the user about obstacles and their proximity through audio messages from the phone, guiding them along a safe path to their destination. The system is designed to be low-cost and portable to help address mobility challenges faced by many visually impaired individuals.
The document describes a hand gesture recognition system for deaf persons to communicate their thoughts to others. It aims to bridge the communication gap between deaf-mute people and the general public by converting gestures captured in real-time via camera, which are trained using a convolutional neural network (CNN), into text output. The system allows deaf-mute users to interact with computer applications using gestures detected by their webcam without needing to install additional applications. It discusses the background and relevance of the project, as well as objectives like designing the gesture training, extracting features from images, and recognizing gestures to translate them to text.
The document describes a hand gesture recognition system for deaf persons to communicate their thoughts to others. It aims to bridge the communication gap between deaf-mute people and the general public by converting gestures captured in real-time via camera, which are trained using a convolutional neural network (CNN), into text output. The system allows deaf-mute users to interact with computer applications using gestures detected by their webcam without needing to install additional applications. It discusses the background and relevance of the project, as well as objectives like designing the gesture training, extracting features from images, and recognizing gestures to translate them to text.
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Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
Neural network optimizer of proportional-integral-differential controller par...IJECEIAES
Wide application of proportional-integral-differential (PID)-regulator in industry requires constant improvement of methods of its parameters adjustment. The paper deals with the issues of optimization of PID-regulator parameters with the use of neural network technology methods. A methodology for choosing the architecture (structure) of neural network optimizer is proposed, which consists in determining the number of layers, the number of neurons in each layer, as well as the form and type of activation function. Algorithms of neural network training based on the application of the method of minimizing the mismatch between the regulated value and the target value are developed. The method of back propagation of gradients is proposed to select the optimal training rate of neurons of the neural network. The neural network optimizer, which is a superstructure of the linear PID controller, allows increasing the regulation accuracy from 0.23 to 0.09, thus reducing the power consumption from 65% to 53%. The results of the conducted experiments allow us to conclude that the created neural superstructure may well become a prototype of an automatic voltage regulator (AVR)-type industrial controller for tuning the parameters of the PID controller.
An improved modulation technique suitable for a three level flying capacitor ...IJECEIAES
This research paper introduces an innovative modulation technique for controlling a 3-level flying capacitor multilevel inverter (FCMLI), aiming to streamline the modulation process in contrast to conventional methods. The proposed
simplified modulation technique paves the way for more straightforward and
efficient control of multilevel inverters, enabling their widespread adoption and
integration into modern power electronic systems. Through the amalgamation of
sinusoidal pulse width modulation (SPWM) with a high-frequency square wave
pulse, this controlling technique attains energy equilibrium across the coupling
capacitor. The modulation scheme incorporates a simplified switching pattern
and a decreased count of voltage references, thereby simplifying the control
algorithm.
A review on features and methods of potential fishing zoneIJECEIAES
This review focuses on the importance of identifying potential fishing zones in seawater for sustainable fishing practices. It explores features like sea surface temperature (SST) and sea surface height (SSH), along with classification methods such as classifiers. The features like SST, SSH, and different classifiers used to classify the data, have been figured out in this review study. This study underscores the importance of examining potential fishing zones using advanced analytical techniques. It thoroughly explores the methodologies employed by researchers, covering both past and current approaches. The examination centers on data characteristics and the application of classification algorithms for classification of potential fishing zones. Furthermore, the prediction of potential fishing zones relies significantly on the effectiveness of classification algorithms. Previous research has assessed the performance of models like support vector machines, naïve Bayes, and artificial neural networks (ANN). In the previous result, the results of support vector machine (SVM) were 97.6% more accurate than naive Bayes's 94.2% to classify test data for fisheries classification. By considering the recent works in this area, several recommendations for future works are presented to further improve the performance of the potential fishing zone models, which is important to the fisheries community.
Electrical signal interference minimization using appropriate core material f...IJECEIAES
As demand for smaller, quicker, and more powerful devices rises, Moore's law is strictly followed. The industry has worked hard to make little devices that boost productivity. The goal is to optimize device density. Scientists are reducing connection delays to improve circuit performance. This helped them understand three-dimensional integrated circuit (3D IC) concepts, which stack active devices and create vertical connections to diminish latency and lower interconnects. Electrical involvement is a big worry with 3D integrates circuits. Researchers have developed and tested through silicon via (TSV) and substrates to decrease electrical wave involvement. This study illustrates a novel noise coupling reduction method using several electrical involvement models. A 22% drop in electrical involvement from wave-carrying to victim TSVs introduces this new paradigm and improves system performance even at higher THz frequencies.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Bibliometric analysis highlighting the role of women in addressing climate ch...IJECEIAES
Fossil fuel consumption increased quickly, contributing to climate change
that is evident in unusual flooding and draughts, and global warming. Over
the past ten years, women's involvement in society has grown dramatically,
and they succeeded in playing a noticeable role in reducing climate change.
A bibliometric analysis of data from the last ten years has been carried out to
examine the role of women in addressing the climate change. The analysis's
findings discussed the relevant to the sustainable development goals (SDGs),
particularly SDG 7 and SDG 13. The results considered contributions made
by women in the various sectors while taking geographic dispersion into
account. The bibliometric analysis delves into topics including women's
leadership in environmental groups, their involvement in policymaking, their
contributions to sustainable development projects, and the influence of
gender diversity on attempts to mitigate climate change. This study's results
highlight how women have influenced policies and actions related to climate
change, point out areas of research deficiency and recommendations on how
to increase role of the women in addressing the climate change and
achieving sustainability. To achieve more successful results, this initiative
aims to highlight the significance of gender equality and encourage
inclusivity in climate change decision-making processes.
Voltage and frequency control of microgrid in presence of micro-turbine inter...IJECEIAES
The active and reactive load changes have a significant impact on voltage
and frequency. In this paper, in order to stabilize the microgrid (MG) against
load variations in islanding mode, the active and reactive power of all
distributed generators (DGs), including energy storage (battery), diesel
generator, and micro-turbine, are controlled. The micro-turbine generator is
connected to MG through a three-phase to three-phase matrix converter, and
the droop control method is applied for controlling the voltage and
frequency of MG. In addition, a method is introduced for voltage and
frequency control of micro-turbines in the transition state from gridconnected mode to islanding mode. A novel switching strategy of the matrix
converter is used for converting the high-frequency output voltage of the
micro-turbine to the grid-side frequency of the utility system. Moreover,
using the switching strategy, the low-order harmonics in the output current
and voltage are not produced, and consequently, the size of the output filter
would be reduced. In fact, the suggested control strategy is load-independent
and has no frequency conversion restrictions. The proposed approach for
voltage and frequency regulation demonstrates exceptional performance and
favorable response across various load alteration scenarios. The suggested
strategy is examined in several scenarios in the MG test systems, and the
simulation results are addressed.
Enhancing battery system identification: nonlinear autoregressive modeling fo...IJECEIAES
Precisely characterizing Li-ion batteries is essential for optimizing their
performance, enhancing safety, and prolonging their lifespan across various
applications, such as electric vehicles and renewable energy systems. This
article introduces an innovative nonlinear methodology for system
identification of a Li-ion battery, employing a nonlinear autoregressive with
exogenous inputs (NARX) model. The proposed approach integrates the
benefits of nonlinear modeling with the adaptability of the NARX structure,
facilitating a more comprehensive representation of the intricate
electrochemical processes within the battery. Experimental data collected
from a Li-ion battery operating under diverse scenarios are employed to
validate the effectiveness of the proposed methodology. The identified
NARX model exhibits superior accuracy in predicting the battery's behavior
compared to traditional linear models. This study underscores the
importance of accounting for nonlinearities in battery modeling, providing
insights into the intricate relationships between state-of-charge, voltage, and
current under dynamic conditions.
Smart grid deployment: from a bibliometric analysis to a surveyIJECEIAES
Smart grids are one of the last decades' innovations in electrical energy.
They bring relevant advantages compared to the traditional grid and
significant interest from the research community. Assessing the field's
evolution is essential to propose guidelines for facing new and future smart
grid challenges. In addition, knowing the main technologies involved in the
deployment of smart grids (SGs) is important to highlight possible
shortcomings that can be mitigated by developing new tools. This paper
contributes to the research trends mentioned above by focusing on two
objectives. First, a bibliometric analysis is presented to give an overview of
the current research level about smart grid deployment. Second, a survey of
the main technological approaches used for smart grid implementation and
their contributions are highlighted. To that effect, we searched the Web of
Science (WoS), and the Scopus databases. We obtained 5,663 documents
from WoS and 7,215 from Scopus on smart grid implementation or
deployment. With the extraction limitation in the Scopus database, 5,872 of
the 7,215 documents were extracted using a multi-step process. These two
datasets have been analyzed using a bibliometric tool called bibliometrix.
The main outputs are presented with some recommendations for future
research.
Use of analytical hierarchy process for selecting and prioritizing islanding ...IJECEIAES
One of the problems that are associated to power systems is islanding
condition, which must be rapidly and properly detected to prevent any
negative consequences on the system's protection, stability, and security.
This paper offers a thorough overview of several islanding detection
strategies, which are divided into two categories: classic approaches,
including local and remote approaches, and modern techniques, including
techniques based on signal processing and computational intelligence.
Additionally, each approach is compared and assessed based on several
factors, including implementation costs, non-detected zones, declining
power quality, and response times using the analytical hierarchy process
(AHP). The multi-criteria decision-making analysis shows that the overall
weight of passive methods (24.7%), active methods (7.8%), hybrid methods
(5.6%), remote methods (14.5%), signal processing-based methods (26.6%),
and computational intelligent-based methods (20.8%) based on the
comparison of all criteria together. Thus, it can be seen from the total weight
that hybrid approaches are the least suitable to be chosen, while signal
processing-based methods are the most appropriate islanding detection
method to be selected and implemented in power system with respect to the
aforementioned factors. Using Expert Choice software, the proposed
hierarchy model is studied and examined.
Enhancing of single-stage grid-connected photovoltaic system using fuzzy logi...IJECEIAES
The power generated by photovoltaic (PV) systems is influenced by
environmental factors. This variability hampers the control and utilization of
solar cells' peak output. In this study, a single-stage grid-connected PV
system is designed to enhance power quality. Our approach employs fuzzy
logic in the direct power control (DPC) of a three-phase voltage source
inverter (VSI), enabling seamless integration of the PV connected to the
grid. Additionally, a fuzzy logic-based maximum power point tracking
(MPPT) controller is adopted, which outperforms traditional methods like
incremental conductance (INC) in enhancing solar cell efficiency and
minimizing the response time. Moreover, the inverter's real-time active and
reactive power is directly managed to achieve a unity power factor (UPF).
The system's performance is assessed through MATLAB/Simulink
implementation, showing marked improvement over conventional methods,
particularly in steady-state and varying weather conditions. For solar
irradiances of 500 and 1,000 W/m2
, the results show that the proposed
method reduces the total harmonic distortion (THD) of the injected current
to the grid by approximately 46% and 38% compared to conventional
methods, respectively. Furthermore, we compare the simulation results with
IEEE standards to evaluate the system's grid compatibility.
Enhancing photovoltaic system maximum power point tracking with fuzzy logic-b...IJECEIAES
Photovoltaic systems have emerged as a promising energy resource that
caters to the future needs of society, owing to their renewable, inexhaustible,
and cost-free nature. The power output of these systems relies on solar cell
radiation and temperature. In order to mitigate the dependence on
atmospheric conditions and enhance power tracking, a conventional
approach has been improved by integrating various methods. To optimize
the generation of electricity from solar systems, the maximum power point
tracking (MPPT) technique is employed. To overcome limitations such as
steady-state voltage oscillations and improve transient response, two
traditional MPPT methods, namely fuzzy logic controller (FLC) and perturb
and observe (P&O), have been modified. This research paper aims to
simulate and validate the step size of the proposed modified P&O and FLC
techniques within the MPPT algorithm using MATLAB/Simulink for
efficient power tracking in photovoltaic systems.
Adaptive synchronous sliding control for a robot manipulator based on neural ...IJECEIAES
Robot manipulators have become important equipment in production lines, medical fields, and transportation. Improving the quality of trajectory tracking for
robot hands is always an attractive topic in the research community. This is a
challenging problem because robot manipulators are complex nonlinear systems
and are often subject to fluctuations in loads and external disturbances. This
article proposes an adaptive synchronous sliding control scheme to improve trajectory tracking performance for a robot manipulator. The proposed controller
ensures that the positions of the joints track the desired trajectory, synchronize
the errors, and significantly reduces chattering. First, the synchronous tracking
errors and synchronous sliding surfaces are presented. Second, the synchronous
tracking error dynamics are determined. Third, a robust adaptive control law is
designed,the unknown components of the model are estimated online by the neural network, and the parameters of the switching elements are selected by fuzzy
logic. The built algorithm ensures that the tracking and approximation errors
are ultimately uniformly bounded (UUB). Finally, the effectiveness of the constructed algorithm is demonstrated through simulation and experimental results.
Simulation and experimental results show that the proposed controller is effective with small synchronous tracking errors, and the chattering phenomenon is
significantly reduced.
Remote field-programmable gate array laboratory for signal acquisition and de...IJECEIAES
A remote laboratory utilizing field-programmable gate array (FPGA) technologies enhances students’ learning experience anywhere and anytime in embedded system design. Existing remote laboratories prioritize hardware access and visual feedback for observing board behavior after programming, neglecting comprehensive debugging tools to resolve errors that require internal signal acquisition. This paper proposes a novel remote embeddedsystem design approach targeting FPGA technologies that are fully interactive via a web-based platform. Our solution provides FPGA board access and debugging capabilities beyond the visual feedback provided by existing remote laboratories. We implemented a lab module that allows users to seamlessly incorporate into their FPGA design. The module minimizes hardware resource utilization while enabling the acquisition of a large number of data samples from the signal during the experiments by adaptively compressing the signal prior to data transmission. The results demonstrate an average compression ratio of 2.90 across three benchmark signals, indicating efficient signal acquisition and effective debugging and analysis. This method allows users to acquire more data samples than conventional methods. The proposed lab allows students to remotely test and debug their designs, bridging the gap between theory and practice in embedded system design.
Detecting and resolving feature envy through automated machine learning and m...IJECEIAES
Efficiently identifying and resolving code smells enhances software project quality. This paper presents a novel solution, utilizing automated machine learning (AutoML) techniques, to detect code smells and apply move method refactoring. By evaluating code metrics before and after refactoring, we assessed its impact on coupling, complexity, and cohesion. Key contributions of this research include a unique dataset for code smell classification and the development of models using AutoGluon for optimal performance. Furthermore, the study identifies the top 20 influential features in classifying feature envy, a well-known code smell, stemming from excessive reliance on external classes. We also explored how move method refactoring addresses feature envy, revealing reduced coupling and complexity, and improved cohesion, ultimately enhancing code quality. In summary, this research offers an empirical, data-driven approach, integrating AutoML and move method refactoring to optimize software project quality. Insights gained shed light on the benefits of refactoring on code quality and the significance of specific features in detecting feature envy. Future research can expand to explore additional refactoring techniques and a broader range of code metrics, advancing software engineering practices and standards.
Smart monitoring technique for solar cell systems using internet of things ba...IJECEIAES
Rapidly and remotely monitoring and receiving the solar cell systems status parameters, solar irradiance, temperature, and humidity, are critical issues in enhancement their efficiency. Hence, in the present article an improved smart prototype of internet of things (IoT) technique based on embedded system through NodeMCU ESP8266 (ESP-12E) was carried out experimentally. Three different regions at Egypt; Luxor, Cairo, and El-Beheira cities were chosen to study their solar irradiance profile, temperature, and humidity by the proposed IoT system. The monitoring data of solar irradiance, temperature, and humidity were live visualized directly by Ubidots through hypertext transfer protocol (HTTP) protocol. The measured solar power radiation in Luxor, Cairo, and El-Beheira ranged between 216-1000, 245-958, and 187-692 W/m 2 respectively during the solar day. The accuracy and rapidity of obtaining monitoring results using the proposed IoT system made it a strong candidate for application in monitoring solar cell systems. On the other hand, the obtained solar power radiation results of the three considered regions strongly candidate Luxor and Cairo as suitable places to build up a solar cells system station rather than El-Beheira.
An efficient security framework for intrusion detection and prevention in int...IJECEIAES
Over the past few years, the internet of things (IoT) has advanced to connect billions of smart devices to improve quality of life. However, anomalies or malicious intrusions pose several security loopholes, leading to performance degradation and threat to data security in IoT operations. Thereby, IoT security systems must keep an eye on and restrict unwanted events from occurring in the IoT network. Recently, various technical solutions based on machine learning (ML) models have been derived towards identifying and restricting unwanted events in IoT. However, most ML-based approaches are prone to miss-classification due to inappropriate feature selection. Additionally, most ML approaches applied to intrusion detection and prevention consider supervised learning, which requires a large amount of labeled data to be trained. Consequently, such complex datasets are impossible to source in a large network like IoT. To address this problem, this proposed study introduces an efficient learning mechanism to strengthen the IoT security aspects. The proposed algorithm incorporates supervised and unsupervised approaches to improve the learning models for intrusion detection and mitigation. Compared with the related works, the experimental outcome shows that the model performs well in a benchmark dataset. It accomplishes an improved detection accuracy of approximately 99.21%.
Literature Review Basics and Understanding Reference Management.pptxDr Ramhari Poudyal
Three-day training on academic research focuses on analytical tools at United Technical College, supported by the University Grant Commission, Nepal. 24-26 May 2024
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Sinan from the Delivery Hero mobile infrastructure engineering team shares a deep dive into performance acceleration with Gradle build cache optimizations. Sinan shares their journey into solving complex build-cache problems that affect Gradle builds. By understanding the challenges and solutions found in our journey, we aim to demonstrate the possibilities for faster builds. The case study reveals how overlapping outputs and cache misconfigurations led to significant increases in build times, especially as the project scaled up with numerous modules using Paparazzi tests. The journey from diagnosing to defeating cache issues offers invaluable lessons on maintaining cache integrity without sacrificing functionality.
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTjpsjournal1
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
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politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
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objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
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Cooperation Organisation and the Belt and Road Economic Initiative.
The CBC machine is a common diagnostic tool used by doctors to measure a patient's red blood cell count, white blood cell count and platelet count. The machine uses a small sample of the patient's blood, which is then placed into special tubes and analyzed. The results of the analysis are then displayed on a screen for the doctor to review. The CBC machine is an important tool for diagnosing various conditions, such as anemia, infection and leukemia. It can also help to monitor a patient's response to treatment.
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In this paper, we tried to develop a variety of wearable assistive aids for the visually impaired to
eliminate the inconvenience of walking or real life. In order to do this, in Phase I, Maximally Stable External
Region (MSER) and Stroke Width Transform (SWT) features were applied to character recognition of road
signs and pedestrian signs [7, 8]. In Phase II, we tried to design a text recognition system based on TTS
(Text-to-Speech) converter [9] that transmits the text recognition information to the visually impaired.
This paper proposes a plan for the visually impaired to meet these developments and to present
the applicable possibilities. Section 2 briefly discusses the related works for character string recognition
technology currently in development for the visually impaired and characteristics of information guiding
system. Section 3 describes experimental implementation of character recognition for our proposed system.
Sections 4 and 5 conclude the paper by discussing experimental results, future works and other possible
solutions.
2. RELATED WORK
2.1. Characteristics and trend of information guiding system
Blind people are divided into low vision and the blind. Low vision refers to vision problems that
cannot be improved by medical or optical means due to birth defects or acquired eye diseases. According to
a report of Yonsei University Medical Center, the suicide rate of the low vision is twice that of the normal
person, and the psychological stress due to the low vision is large, and the need for an auxiliary device to
help the low vision is increasing [10]. In addition, a report from the UN estimates that the world‟s population
age 60 or older will increase from 11% in 2012 to 22% by 2020 as shown in Figure 1. Especially in North
America and Europe, the distribution of population aged 60 years or older is reported to be significantly
higher than the average [11]. In the point of world market, Figure 2 indicated that the global elderly and
disabled assistive devices market was valued at US$ 14,109.1 million in 2015 and is expected to expand at
a CAGR of 7.4% during the forecast period (2016 – 2024) [12].
Figure 1. The statistcs of UN, gendered innovations (2012 vs. 2050) [11]
Figure 2. Global elderly and disabled assistive devices market size and forecast (unit: US$ Million) [12]
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2.2. Character information recognition system
To allow a visually impared person to recognize a character, our application must be able to find
the character region in which the sign or the message is written. The most well-known method used for
binarization is a global binarization which is based on a single threshold [13-15]. However, these methods
have chracteristics such as performance issues with the overall brightness of the input document image are
not constant.
Another method used for binarization is the Maximally Stable External Region (MSER) algorithm,
which is used in a more robust manner of finding a region with a small rate of change while changing the
threshold value in order to distinguish characters in both bright and dark regions. The character area is
generally easy to distinguish from the background and has a constant brightness value. This characteristic of
the character region is suitable to be detected by the MSER method [7, 8]. Various applications have been
developed by various companies, all of which attempt to extract a character string by extracting horizontal
and vertical boundary components from the input image. These methods basically either find the portion with
the greatest boundary component or extract a character string that is irrespective of misjudgment or
distortion.
The ABBYY FineReader Engine, OCR SDK (character recognition development toolkit) supplied
by Retia, was applied to the development of a 'print-to-speech converter', which is a device for recognizing
printed characters for visually impaired and converting them into voice [16-18]. ABBYY [19] developed
ABBYY FineReader Engine with a goal of a stable „print-to-speech‟ converter for the visually impaired.
The OCR key technologies of ABBYY FineReader Engine have several main features such as:
a. Korean, Chinese, English, numbers and special characters support
b. Vertical reading, Multi reading
c. Batch scanning, batch conversion possible
d. It can save word, text file etc.
By utilizing this engine, the visually impaired user can convert the desired document to speech
through this device. While in the past books, receipts and other readable documents could not be read without
Braille documents, the engine now makes it possible to directly scan a desired document or image by using
the „sound‟ with OCR technology and convert it so the user can hear the by voice. The „finger reader‟ [20]
product developed by MIT works by placing a finger near the book. A high-resolution camera is used to scan
the characters corresponding to the finger‟s touch while also reading them out loud after being scanned. After
several years of research, OrCam, an Israeli company, is now developing new products that use facial
recognition technology to scan not only characters but also various colors [21]. There are also „smart glasses‟
for people with partial vision loss. These „smart glasses‟ work by viewing images in 3D glasses. However
even though these glasses have been proven useful reducing inconvenience of the visually disabled, they are
still very expensive. Therefore there will be difficulties in making them commercially available for everyone.
Figure 3 shows the number of people in Korea with sight disabilities is around about 250,000 people as of
2016. Unfortunately, the number of people with visual disabilities is growing larger each year by more than
10%. In addition, the types of disabilities are discribed in Figure 4.
Figure 3. The statistics of disabilities in Korea, 2007 and 2016 [22]
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Figure 4. The types of visually impaired. (a) Scenery seen with normal eye, (b) Scenery seen with eyes with
cataracts, (c) Scenery seen with eyes with glaucoma, (d) Scenery seen with eyes with diabetic retinopathy,
(e) Scenery seen with eyes with macular degeneration [23]
3. EXPERIMENTAL IMPLEMENTATION
One of the most important parts of the application is to provide information that is only necessary in
order to never confuse the user. Therefore, the application must be able to select only the relevant area
amongst the other „background noise‟. For example, the application must be able to distinguish between
a road sign and the other natural background surrounding the sign. In this paper, we aim to detect the text
area in the image provided with the visually impaired and to recognize the information provided in the area
as a character and deliver it to the visually impaired. In order to implement our goal, we used MSER and
OCR methods for detecting information area and text detection as a starting point of research. Based on
the Phase I of the research, we aim to develop a wearable device that provides road information about
the visually impaired by utilizing the TTS (Text-to-Speech) function of a typical smartphone.
3.1. Feature extraction with MSER
Information on the road signs do not contain as much textual information when compared to books
or newspapers. As a method of the visually impaired to arrive at their desired destination, they had to
previous rely the usage of a guidance stick. While it may to practical and has been used as from
the beginning of blind people, a different method can be developed. These days it is possible to detect
the text in an image using no more than a smartphone with a camera. By using pixel spans as nodes, blobs
can be generated which can detect text in an image more quickly and accurately. In addition, as the usage of
smartphone increased very rapidly, an optical character recognition application that recognizes a character of
an image captured by a camera mounted on a smart phone and displays it on a display can be distributed in
the near future and prove more practical compared to a guidance stick.
The most important step is to detect the blob which does a candidate region exists in the image that
is most likely to contain the text of the road sign. The SWT algorithm [24, 25] is a method of detecting text
by determining which region has little change in the shape and thickness. When the parameters are given,
the algorithm detects the text within the image using those parameters. The main advantage of SWT are that
it can detect text in an image without a separate learning process, but it also has a drawback in which it takes
a lot of time to detect text in an image because of its complicated operation. The MSER algorithm for robust
text detection is widely used as an algorithm for detecting blob as an aggregate region of pixels different
from surrounding pixels in intensity. The MSER algorithm has the advantage that it can detect the blob faster
than the SWT algorithm, but it has a disadvantage that the accuracy is somewhat lacking, such as detecting
the tickle or noise by blob.
3.2. Application procedure
Figure 5 is an overall block diagram that shows the process of our application after capturing
the image and extracting the text. In this paper, we aimed to test the design possibility of an assistive device
which can be helpful for the visually impaired through Phase I process in two stages. The first step captures
images of a smartphone or future terminal device that the blind has and then removes non-text regions using
MSER. The MSER extraction implements the following steps:
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Figure 5. The overall block diagram
a. Sweep threshold of intensity
b. Extract connected components
c. Find a threshold on maximally stable
d. Approximate a region with an ellipse
e. Keep region descriptors
One of the most important features of the MSER algorithm is that it detects most text in an image
but also extracts a stable region, not a text region. To make the algorithm suit our needs, we removed non-
text areas using parameters that distinguish words by their geometrical properties within the image.
In addition, SWT can be used to distinguish more sophisticated non-text areas. In this paper, we applied this
method to find and remove non-text areas. In order to merge individual text areas to extract information on
a single word or a text line after finally confirming the text area, a neighboring text area is searched to form
a bounding box of these areas, and finally, the information is extracted. In Phase II, the final detected text
information is converted into voice information on the visually impaired to be transmitted or applied to future
applicable and wearable devices.
4. RESULT AND DISCUSSION
4.1. Phase I
In our experiment, we used a typical image of the road sign which the visually impaired can easily
encounter on the road. The left column of Figure 6 shows test data set. These images were sorted in order to
make test conditions more difficult. When comparing the amount of text to the whole image there is not
much text contained in the image in the first place. Therefore, these images were ideal in testing if our
proposed method of combining MSER and SWT to extract the necessary information. These test conditions
were also important because the end goal of our application is to distribute it so that it can be used during
everyday activities. Thus, we made sure that the images were selected very carefully in order to simulate
what the user might encounter while using the application.
In Figure 6, we show the results of applying MSER, geometric characteristics, and then applying
SWT to find non-text areas in captured images using mobile phones of the visually impaired. These results
are shown on right column of Figure 6 and Table 1 shows the final detected character information of each
test image. In our test case of images containing only English characters, accuracy was high in
the implemented method. However, when we applied our method to an image where Korean and English
were mixed, we could see a drop off in performance. Through this result we can confirm that a different
detection engine is required for the detection of multiple languages.
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(a) (b) (c) (d)
(e) (f) (g) (h)
Figure 6. The test data set and experimental results
Table 1. Implemental and detected results
Test data Detected Text Information
Figure 6-(a)
Cyclists
AHEAD
SLOW
Figure 6-(c) AHEAD
Figure 6-(e)
PED
XING
Figure 6-(g)
‟.„i".Si6
SLOW
4.2. Phase II
TTS is a type of speech synthesis program that makes the contents of computer documents, such as
help files and web pages, sound human-readable. TTS can also read image information for people with visual
impairments. There are many TTS products on the market, including Read Please 2000, Proverbe Speech
Unit, and TextAloud. Lucent and AT & T have their own products called “Text-to-Speech.” In this research,
we applied Microsoft Speech API's speech to text functionality in consideration of efficient aspects [26].
Figure 7 shows simplified block diagram for TTS function. This system works well for our test data.
(a) (b) (c)
Figure 7. The block diagram for text-to-speech process. (a) input image,
(b) captured letters on notepad, and (c) speech out with text.txt file
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5. CONCLUSION
In this paper, we proposed a character recognition system for visual impaired persons and added in
a voice guidance application implementation process. Our goal is to add a character recognition system for
the visually impaired to the smartphone terminal through H/W production. We proposed a method to detect
the characters and apply the voice guidance from the images captured in Phase I. Using the features of MSER
and SWT, it showed the possibility of extracting the letters of road signs, and in Phase II, it showed the result
of delivering the extracted text information to the users.
However, in this paper, we can look at various future points to consider. So far, the road guidance
service application for the visually impaired has been developed using a blue pitcher communication based
H/W auxiliary device such as a beacon in a specific area. With the development of IoT technology,
the objects and data related to IoT have been increased greatly. It is necessary to develop a camera-based
video information guidance service app that utilizes a voice guidance service technology that provides
appropriate information. In addition, artificial intelligence techniques such as image recognition, natural
language processing, and natural language generation can be used to enable blind people to live a more
comprehensive and productive life.
ACKNOWLEDGEMENTS
This research was supported by the Daegu University Research Grant, 2017.
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BIOGRAPHIES OF AUTHORS
Jaejoon Kim received the MS and Ph.D. degree from the Department of Electrical Engineering,
Iowa State University, USA. He received Bachelors from Department Electronics Engineering
and Mathematics, Hanyang University, Korea. From 2001 to 2002, he was a senior researcher at
ETRI (Electronics and Telecommunication Research Institute). He is currently a professor at
Daegu University, Republic of Korea. His research interests include image processing, neural
networks and non-destructive evaluation.