DocumentCode :
2029990
Title :
The reduction of memory and the improvement of recognition rate for HMM on-line handwriting recognition
Author :
Funada, A. ; Muramatsu, D. ; Matsumoto, T.
Author_Institution :
Dept. of Electr. Eng., & Bioscience, Waseda Univ., Tokyo, Japan
fYear :
2004
fDate :
26-29 Oct. 2004
Firstpage :
383
Lastpage :
388
Abstract :
The purpose of this project is two fold. The first purpose is to reduce the memory size of our previous handwriting recognition algorithm based on an HMM using self-organizing map (SOM) density tying. The second is to improve recognition capability by incorporating additional information. SOM density tying reduced the dictionary size to 1/7 of the original size, with a recognition rate of 90.45%, only slightly less than the original recognition rate of 91.51%. Our additional feature increased recognition capability to 91.34%.
Keywords :
handwriting recognition; hidden Markov models; self-organising feature maps; hidden Markov model; online handwriting recognition; self-organizing map; Character recognition; Degradation; Dictionaries; Handwriting recognition; Hardware; Hidden Markov models; Keyboards; Personal digital assistants; Vector quantization; Writing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Frontiers in Handwriting Recognition, 2004. IWFHR-9 2004. Ninth International Workshop on
ISSN :
1550-5235
Print_ISBN :
0-7695-2187-8
Type :
conf
DOI :
10.1109/IWFHR.2004.102
Filename :
1363941
Link To Document :
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