Title :
Multilayer fuzzy HMM for online handwriting shape recognition
Author :
Li, Cuiyun ; Ji, Hongbing ; Pei, Jihong
Author_Institution :
Sch. of Electr. Eng., Xidian Univ., Xi´´an, China
fDate :
31 Aug.-4 Sept. 2004
Abstract :
This paper discusses a novel type of fuzzy hidden Markov model (FHMM) based on a multilayer 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 multilayer FHMM can decrease the computation time in training because of the fuzziness of the model. Due to the reduction of the shape searching space by the decision tree, the recognition time is saved and the recognition rate is improved.
Keywords :
decision trees; fuzzy set theory; handwritten character recognition; hidden Markov models; learning (artificial intelligence); FHMM; FHMM training; decision tree; fuzzy hidden Markov model; local feature vector; multilayer decision tree; online handwriting shape recognition; shape searching space; Character recognition; Decision trees; Density measurement; Handwriting recognition; Hidden Markov models; Logic; Robustness; Shape; Spatial databases; Speech;
Conference_Titel :
Signal Processing, 2004. Proceedings. ICSP '04. 2004 7th International Conference on
Print_ISBN :
0-7803-8406-7
DOI :
10.1109/ICOSP.2004.1441594
