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dc.contributor.advisorYan, Wei Qi
dc.contributor.authorLi, Ricky
dc.date.accessioned2017-10-23T21:41:58Z
dc.date.available2017-10-23T21:41:58Z
dc.date.copyright2017
dc.date.created2017
dc.identifier.urihttp://hdl.handle.net/10292/10892
dc.description.abstractThe Morse code is one of the earliest means of telecommunications; however, it is rarely used nowadays due to viral mobile communications. Although a person can tap Morse codes using his fingers easily, perhaps nobody is aware of this kind of finger gestures anymore. In this thesis, we will develop a prototype combined the principle of old Morse code with finger gesture recognition in machine learning together. A camera is used to capture a sequence of video frames, the prototype will recognize the finger gestures from these frames and convert the corresponding Morse codes to readable ASCII letters, characters or emotional symbols. The significant work could be applied to those special communications or dialogues, not allowed to speak loudly and explicitly. The contributions of this thesis are the finger gesture recognition based on empirical approaches for Morse code input; the highest recognition rate is up to 93%.en_NZ
dc.language.isoenen_NZ
dc.publisherAuckland University of Technology
dc.subjectGesture recognitionen_NZ
dc.subjectMorse codeen_NZ
dc.subjectFingertip trackingen_NZ
dc.subjectSVM (support vector machine)en_NZ
dc.subjectGaussian pyramiden_NZ
dc.subjectBPNNen_NZ
dc.titleComputer Input of Morse Codes Using Finger Gesture Recognitionen_NZ
dc.typeThesis
thesis.degree.grantorAuckland University of Technology
thesis.degree.levelMasters Theses
thesis.degree.nameMaster of Computer and Information Sciencesen_NZ
dc.rights.accessrightsOpenAccess
dc.date.updated2017-10-20T06:55:35Z


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