Title :
HMM based online hand-drawn graphic symbol recognition
Author :
Xin, Gong ; Cuiyun, Li ; Jihon, Pei ; Weixin, Xie
Author_Institution :
Sch. of Electron. Eng., Xidian Univ., Xi´´an, China
Abstract :
In this paper, an online hand-drawn graphic symbol recognition algorithm based on hidden Markov models is presented. A rearrangement strategy is applied to the hand-drawn symbol points in order to alleviate the influence of the difference in drawing sequence. Based on rearranged drawing points, global distance measure and local angle feature are extracted as the feature vector. After the quantization, a discrete HMM is used as the core recognizer. The experiment shows the recognition rate of our system can be above 85%.
Keywords :
feature extraction; handwritten character recognition; hidden Markov models; image sequences; discrete HMM; drawing sequence; feature vector; global distance measure; graphic symbol recognition; hidden Markov models; local angle feature extraction; online hand-drawn algorithm; quantization; rearrangement strategy; Automatic speech recognition; Feature extraction; Goniometers; Graphics; Handwriting recognition; Hidden Markov models; Libraries; Pattern recognition; Random processes; Speech recognition;
Conference_Titel :
Signal Processing, 2002 6th International Conference on
Print_ISBN :
0-7803-7488-6
DOI :
10.1109/ICOSP.2002.1179973
