Diagram recognition using hidden Markov models
User input interfaces are quickly become more natural and intuative, relying less and less on the traditional mouse and keyboard interface, and moving towards a pen based input system. Current technologies which take advancement of these developments in hardware have been based primarily on handwriting recognition to allow the user to write there instructions instead of typing. Some work has been performed regarding diagram recognition from on-line input, however these system have been developed using hardcoded parameters with fuzzy sets and common feature sets. Hidden Markov Models are a powerful mathematical recognition tool, which is current being used in feilds such as speech recognition, handwriting recognition and DNA cell searching and classification applications. This is the first attempt at using a hidden markov model to recognize input from a two dimensonal spacial environment, the result of the initial implementation have shown promising results for more complex recognition models.
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|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology|
|Copyright Owner:||Copyright 2003 (please consult author)|
|Deposited On:||02 Mar 2005 00:00|
|Last Modified:||09 Jun 2010 12:23|
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