Sabaragamuwa University of Sri Lanka

Sri Lankan Currency Detector for Visually Impaired People

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dc.contributor.author Abimani, R.M.K.C.
dc.contributor.author Thalagahagedara, T.M.S.S.B.
dc.contributor.author Thilakarathna, H.P.M.U.
dc.contributor.author Wickramasingha, S.D.S.B.
dc.contributor.author Nawinna, Dasuni
dc.contributor.author Kasthurirathna, Dharshana
dc.date.accessioned 2021-07-02T13:23:47Z
dc.date.available 2021-07-02T13:23:47Z
dc.date.issued 2021-02-24
dc.identifier.issn 2773-7136
dc.identifier.uri http://repo.lib.sab.ac.lk:8080/xmlui/handle/123456789/1745
dc.description.abstract 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. en_US
dc.language.iso en en_US
dc.publisher Department of Computing and Information Systems, Faculty of Applied Sciences, Sabaragamuwa University of Sri Lanka, P.O. Box 02, Belihuloya, 70140, Sri Lanka. en_US
dc.subject CONVOLUTIONAL NEURAL NETWORK (CNN) en_US
dc.subject MEL – FREQUENCY CEPSTRAL COEFFICIENT(MFCC) en_US
dc.title Sri Lankan Currency Detector for Visually Impaired People en_US
dc.type Article en_US


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  • ICARC - 2021 [34]
    “Towards a Digitally Empowered Society”

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