Abstract—In this paper, we propose a system for Thai alphabet recognition from hand movement trajectory, as a human-computer interaction method. Thai characters drawing by hand movement are analyzed and recognized by our system, which can apply for controlling any specific tasks. The method is based on hand motion analysis combining with Haar-like with a cascade of boost classifiers, as hand detection method. Hand is tracked with skin color using Cam Shift and Kalman filter. Trajectory features of hand are extracted and used for recognizing 12 Thai alphabets though the Hidden Markov Model.
Index Terms—Hand Movement Trajectory, Hand Gesture Recognition using HMM, Thai Alphabet Recognition.
Kittasil Silanon is with the Department of Computer Engineering, Faculty of Engineering, Prince of Songkla University, P.O. Box 2 Kohong, Hatyai, Songkla 90112 Thailand (e-mail: jalego3@hotmail.com).
Nikom Suvonvorn is with the Department of Computer Engineering, Faculty of Engineering, Prince of Songkla University, P.O. Box 2 Kohong, Hatyai, Songkla 90112 Thailand (e-mail: kom@coe.psu.ac.th).
Cite: Kittasil Silanon and Nikom Suvonvorn, "Hand Motion Analysis for Thai Alphabet Recognition using HMM," International Journal of Information and Electronics Engineering vol. 1, no. 1, pp. 65-71, 2011.