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A real time sign language alphabetical identifier mobile application using image processing technique / Siti Aisyah Muhamad Roslan Paul Wyman

Sign language is a native language for deaf people and hearing people need to learn it if they want to communicate with deaf people smoothly. Learning sign language in class for normal people is limited because most of the class are reserved for the people and it takes time to master in using it. Cu...

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Main Author: Muhamad Roslan Paul Wyman, Siti Aisyah
Format: Student Project
Language:English
Published: 2019
Subjects:
People with disabilities. Including blind, deaf, people with physical and mental disabilities
Mobile computing
Online Access:https://ir.uitm.edu.my/id/eprint/107710/1/107710.pdf
https://ir.uitm.edu.my/id/eprint/107710/
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id my.uitm.ir.107710
record_format eprints
spelling my.uitm.ir.1077102024-12-16T01:50:11Z https://ir.uitm.edu.my/id/eprint/107710/ A real time sign language alphabetical identifier mobile application using image processing technique / Siti Aisyah Muhamad Roslan Paul Wyman Muhamad Roslan Paul Wyman, Siti Aisyah People with disabilities. Including blind, deaf, people with physical and mental disabilities Mobile computing Sign language is a native language for deaf people and hearing people need to learn it if they want to communicate with deaf people smoothly. Learning sign language in class for normal people is limited because most of the class are reserved for the people and it takes time to master in using it. Current mobile application that help in communicating does not do real time translating. In order to help normal and deaf people to communicate and cut the time in learning, direct translator shoud be develop instead of dictionary because people need to study it first before using it. In this project, it focus on translating the hand sign directly after the image is captured. The hand sign recognition that it will translate is the 26 alphabet in sign language which is A to Z. Technique that will use to recognize the hand sign is image processing technique. After the image is capture, it will detect the edge of the hand sign in the image using edge detecting technique and match with the database. Nowadays, Video Relay Service (VRS) is used as a manual interpreter and also online dictionary. There are many researchers work has been done to automate the process of sign language interpretation. Since camera technology get sophisticated, it will be use to test result of this project. It it hoped that this research could help other researchers for future research. 2019 Student Project NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/107710/1/107710.pdf A real time sign language alphabetical identifier mobile application using image processing technique / Siti Aisyah Muhamad Roslan Paul Wyman. (2019) [Student Project] <http://terminalib.uitm.edu.my/107710.pdf> (Unpublished)
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic People with disabilities. Including blind, deaf, people with physical and mental disabilities
Mobile computing
spellingShingle People with disabilities. Including blind, deaf, people with physical and mental disabilities
Mobile computing
Muhamad Roslan Paul Wyman, Siti Aisyah
A real time sign language alphabetical identifier mobile application using image processing technique / Siti Aisyah Muhamad Roslan Paul Wyman
description Sign language is a native language for deaf people and hearing people need to learn it if they want to communicate with deaf people smoothly. Learning sign language in class for normal people is limited because most of the class are reserved for the people and it takes time to master in using it. Current mobile application that help in communicating does not do real time translating. In order to help normal and deaf people to communicate and cut the time in learning, direct translator shoud be develop instead of dictionary because people need to study it first before using it. In this project, it focus on translating the hand sign directly after the image is captured. The hand sign recognition that it will translate is the 26 alphabet in sign language which is A to Z. Technique that will use to recognize the hand sign is image processing technique. After the image is capture, it will detect the edge of the hand sign in the image using edge detecting technique and match with the database. Nowadays, Video Relay Service (VRS) is used as a manual interpreter and also online dictionary. There are many researchers work has been done to automate the process of sign language interpretation. Since camera technology get sophisticated, it will be use to test result of this project. It it hoped that this research could help other researchers for future research.
format Student Project
author Muhamad Roslan Paul Wyman, Siti Aisyah
author_facet Muhamad Roslan Paul Wyman, Siti Aisyah
author_sort Muhamad Roslan Paul Wyman, Siti Aisyah
title A real time sign language alphabetical identifier mobile application using image processing technique / Siti Aisyah Muhamad Roslan Paul Wyman
title_short A real time sign language alphabetical identifier mobile application using image processing technique / Siti Aisyah Muhamad Roslan Paul Wyman
title_full A real time sign language alphabetical identifier mobile application using image processing technique / Siti Aisyah Muhamad Roslan Paul Wyman
title_fullStr A real time sign language alphabetical identifier mobile application using image processing technique / Siti Aisyah Muhamad Roslan Paul Wyman
title_full_unstemmed A real time sign language alphabetical identifier mobile application using image processing technique / Siti Aisyah Muhamad Roslan Paul Wyman
title_sort real time sign language alphabetical identifier mobile application using image processing technique / siti aisyah muhamad roslan paul wyman
publishDate 2019
url https://ir.uitm.edu.my/id/eprint/107710/1/107710.pdf
https://ir.uitm.edu.my/id/eprint/107710/
_version_ 1818838386542116864
score 13.22586

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