Faculty of Computing

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Subject: search.filters.subject.Visually

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Now showing 1 - 4 of 4
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    Voice-based Online Examination System for Visually Impaired Students
    (IEEE, 2022-04-14) Jayakody, J. A. D. C. A; Dharmasena, I. H. H. N
    Online methods such as e-learning, e-business, online shopping, online payment, and so on have gained in popularity around the world as a result of the COVID 19 pandemic. Education sectors use emergency tele-learning, online learning platforms to persist in this circumstance and exams are conducted as online exams. This research highly focused on visually impaired students who are unable to read the questions displayed on the computer screen in this online examination system. They missed their braille system which is more familiar to read and write more easily. This is high time to build a proper voice-based online examination system for visually impaired students. This system should read the question that is displayed on the screen and obtain the student's response via voice commands. It can only lead students through the online exam using voice, and students can only provide the system answers and navigation orders using voice. The proposed system major goals are to read questions to students, obtain answers from them and effectively navigate students through the system using voice instructions. It builds a comfortable environment for the visually impaired students to write the exam and it helps to improve their personality when they are facing the exam.
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    PublicationEmbargo
    BlindAid - Android-based Mobile Application Guide for Visually Challenged People
    (IEEE, 2021-12-06) Senarathne, G; Punchihewa, D; Liyanage, D. I; Wimalaratne, G; De Silva, H
    Millions of people across the world are affected by visual impairments. The proposed application is designed for visually impaired people consists of three components which are face recognition with emotion, obstacle identification through distance measurement, extract and convey critical information like text, labels, and currency details. Most works reported in the literature depends on the availability of specific hardware. The proposed proof of concept prototype aims to make visually impaired people more independent and carry out tasks conveniently and safely.
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    PublicationEmbargo
    BlindAid-Android-based Mobile Application Guide for Visually Challenged People
    (IEEE, 2021-10-27) Senarathne, G; Punchihewa, D; Liyanage, D. I; Wimalaratne, G; De Silva, H
    Millions of people across the world are affected by visual impairments. The proposed application is designed for visually impaired people consists of three components which are face recognition with emotion, obstacle identification through distance measurement, extract and convey critical information like text, labels, and currency details. Most works reported in the literature depends on the availability of specific hardware. The proposed proof of concept prototype aims to make visually impaired people more independent and carry out tasks conveniently and safely.
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    PublicationOpen Access
    Sri Lankan Currency Detector for Visually Impaired People
    (Department of Computing and Information Systems, Faculty of Applied Sciences, Sabaragamuwa University of Sri Lanka, 2021-02-24) Abimani, R. M. K. C; Thalagahagedara, T. M. S. S. B; Thilakarathna, H. P. M. U; Wickramasingha, S. D. S. B; Nawinna, D. P; Kasthurirathna, D
    Blind people face more difficulties in day to day life. One pressing problem is they also want to use physical currency (notes and coins) as others. They always have a hard time when trying to recognize the value of a currency, we intend to address this matter by developing a mobile application for blind people. We are going to implement this currency recognition mobile application along with counting and voice command compatibility and also this application is having user-friendly interfaces, therefore easy to negotiate. By using this mobile application blind people can give voice commands to navigate and the start intended to function as a currency recognition or counting as a pleased. We are going to use the user’s mobile phone camera to get input into the app then classify the currency as a note or a coin. After that extract the features of the currency note and coin by using Convolutional Neural Network and predicting the value of the currency note and coin. This mobile application can extract the value of the coins and notes without any issue. Finally, we used Artificial Neural Network for the classification of notes and coins. Processing it and get the real value of the notes. Finally, train the Sinhala and English voice command using the CNN model and get them out as a voice