| 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 |