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 |