Development of methodology for Malaysian sign language recognition

Yona Falinie Abdul Gaus (2013) Development of methodology for Malaysian sign language recognition. Masters thesis, Universiti Malaysia Sabah.

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Abstract

Development of Methodology for Malaysian Sign Language Recognition is undertaken on Malaysian Sign Language (MSL) aimed to reduce the challenge faced by the deaf community, while communicating in a normal society by providing a mechanism to translate sign language into words. Therefore, in this thesis, the main focus is on vision-based hand gesture recognition through investigation of each step including frame selection, skin segmentation, trajectory tracking and recognition. There were 112 isolated MSL chosen; each of the sign is performed six times by different signers, making six video sequence databases of MSL. From the six databases, five databases are used for training and one database is used for testing. In frame selection, only selected frames from the video are required to represent the respected signs. Then, skin likelihood model is built first to filter out skin region, which consists of hands and face region from non-skin region. Centroids, distances and orientations of hand skin region are collected as feature vectors. When overlapping between hand-face or hand-hand occurred, Linear Kalman Filter is used to distinguish the separate features. Each of the feature vectors is translated into chain code for the recognition stage using Hidden Markov Model. There will be six maximum logarithmic probability values that are produced representing the respective signs. In the testing stage, these six values need to be summed up in order to check the correct classification value, which is based on the highest logarithmic probability values. The recognition rate using HMM for testing data achieved up to 83.1%.

Item Type:	Thesis (Masters)
Keyword:	Malaysian Sign Language Recognition, Malaysian Sign Language
Subjects:	H Social Sciences > HV Social pathology. Social and public welfare. Criminology > HV1-9960 Social pathology. Social and public welfare. Criminology > HV697-4959 Protection, assistance and relief
Department:	SCHOOL > School of Engineering and Information Technology
Depositing User:	DG MASNIAH AHMAD -
Date Deposited:	04 Dec 2024 15:13
Last Modified:	04 Dec 2024 15:13
URI:	https://eprints.ums.edu.my/id/eprint/41796

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