This diploma thesis deals with handwriting recognition in real-time. It describes the ways how the intput data are processed. It is also focused on the classi cation methods, which are used for the recognition. It especially describes hidden Markov models. It also present the evaluation of the success of the recognition based on implemented experiments. The alternative keyboard for MeeGo system was created for this thesis as well. The established system achieved the success above 96%.
Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:236429 |
Date | January 2012 |
Creators | Zouhar, David |
Contributors | Řezníček, Ivo, Mlích, Jozef |
Publisher | Vysoké učení technické v Brně. Fakulta informačních technologií |
Source Sets | Czech ETDs |
Language | Czech |
Detected Language | English |
Type | info:eu-repo/semantics/masterThesis |
Rights | info:eu-repo/semantics/restrictedAccess |
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