3D handwriting recognition method based on hidden Markov models
基于隐马尔可夫模型的3D手写识别方法

In order to achieve efficient and convenient human-computer interaction, improve interaction ability, this paper proposed a new 3D handwriting recognition method based on HMM. In this method, using of the tri-axis accelerometer mounted on a handheld device to collect various handwriting data; using of the interpolation and FFT filtering to preprocess the data; using of the hidden Markov models to train every handwriting movement ; using of the trained HMM to carry out the handwriting recognition. Tested on the handwriting mobile device, the results show that the classification accuracy can reach 84. 5%.