South African sign language recognition using feature vectors and Hidden Markov Models

South African sign language recognition using feature vectors and Hidden Markov Models

Masters of Science === This thesis presents a system for performing whole gesture recognition for South African Sign Language. The system uses feature vectors combined with Hidden Markov models. In order to constuct a feature vector, dynamic segmentation must occur to extract the signer's hand...

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Bibliographic Details
Main Author: Naidoo, Nathan Lyle
Other Authors: Connan, James
Language:en
Published: University of the Western Cape 2013
Subjects:
Optical pattern recognition
Mathematical models
Image processing
Digital techniques
Markov processes
Online Access:http://hdl.handle.net/11394/2527

Internet

http://hdl.handle.net/11394/2527

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