M.Sc. Tezi Görüntüleme

Student:	Selda BAYRAK
Supervisor:	Prof. Dr. Vasif V. NABIYEV
Department:	Bilgisayar Mühendisliği
Institution:	Graduate School of Natural and Applied Sciences
University:	Karadeniz Technical University, Turkey

Title of the Thesis:	COMPUTER-BASED SIGN LANGUAGE INTERPRETATION
Level:	M.Sc.
Acceptance Date:	16/7/2009
Number of Pages:	60
Registration Number:	i2062

Summary:

In this thesis, it is aimed to interpret sign language used by deaf people based on computer. For this, it is required to determine representations for words used in the sign language and perform classification by using these representations.

First of all, hand motion tracking in the video where datas are extracted from was implemented. For object tracking, mean shift algorithm was used. Thus, change in hand shape in time and trajectory of hand were obtained.

In the next step, the feature vectors were extracted from the obtained trajectory. To extract hand shape feature vectors, Zernike moments were computed.

Finally, hidden Markov model classification was proposed for various types of hand gesture recognition. The decision regarding in recognition was made based on similarity among signs in the trained system.

Keywords: Sign Language, Mean-Shift Algorithm, Zernike Moments, Hidden Markov Model