dc.contributor.author |
Rathnayaka, R. M. K. B |
|
dc.date.accessioned |
2022-03-16T06:16:01Z |
|
dc.date.available |
2022-03-16T06:16:01Z |
|
dc.date.issued |
2021 |
|
dc.identifier.citation |
Rathnayaka, R. M. K. B (2021) iPanther – Sri Lankan sign language converter . BSc. Dissertation Informatics Institute of Technology |
en_US |
dc.identifier.issn |
2017455 |
|
dc.identifier.uri |
http://dlib.iit.ac.lk/xmlui/handle/123456789/1002 |
|
dc.description.abstract |
"
In past years, sign language conversion has become a hot subject in the software
development industry. This can be used to facilitate contact with deaf people and people
who aren't familiar with Sign Language. There is a significant contact distance between
these people due to a lack of understanding of Sign Language. Deaf people become
socially isolated as a result of this. If the deaf person is a child, this will have a greater
impact. And young adults with hearing impairments face difficulties when searching for
jobs and working on the job. When opposed to the job market for ordinary people, the job
market for people with hearing impairments is restricted. As a result, the solution is to
create applications that converts Sri Lankan sign language to Sinhala text and displays it
to the other party in order to bridge the contact gap. Image Processing and Machine
Learning are used to create this application. sign language gestures are first captured and
identified through processing. Then it created terms and displayed them in a Graphical
User Interface to the user." |
en_US |
dc.language.iso |
en |
en_US |
dc.subject |
WHO |
en_US |
dc.subject |
Sri Lankan Sign Language |
en_US |
dc.subject |
OpenCV |
en_US |
dc.subject |
Machine learning |
en_US |
dc.subject |
Image Processing |
en_US |
dc.title |
iPanther – Sri Lankan sign language converter |
en_US |
dc.type |
Thesis |
en_US |