Multi-layer fuzzy HMM for online handwriting shape recognition

被引：0
|
作者：
Li, CY [1 ]
Ji, HB [1 ]
Pei, JH [1 ]
机构：
[1] Xidian Univ, Sch Elect Engn, Xian 710071, Peoples R China
来源：
2004 7TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS, VOLS 1-3 | 2004年
关键词：
online shape recognition; fuzzy HMM; decision tree;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper discusses a novel type of Fuzzy Hidden Markov Model (FHMM) based on a multi-layer decision tree and presents its application to online shape recognition. A local feature vector is obtained by calculating a shape's absolute angle, which is used as the feature for FHMM training and recognition. The global features of the shape are incorporated into the decision tree. The multi-layer FHMM can decrease the computation time in training because of the fuzzyness of the model. Due to the reduction of the shape searching space by the decision tree, the recognition dine is saved and the recognition rate is improved.
引用
收藏
页码：1427 / 1430
页数：4
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