DocumentCode :
1582771
Title :
A distributed scheme for lexicon-driven handwritten word recognition and its application to large vocabulary problems
Author :
Koerich, Alessandro L. ; Sabourin, Robert ; Suen, Ching Y.
Author_Institution :
Lab. d´´Imagerie, de Vision et d´´Intelligence Artificie, Ecole de Technol. Superieure, Montreal, Que., Canada
fYear :
2001
fDate :
6/23/1905 12:00:00 AM
Firstpage :
660
Lastpage :
664
Abstract :
Many offline handwritten word recognition systems have been proposed since the early nineties. Most systems reported high recognition rates, however, they overlooked a very important factor in the process: speed factor. The authors explore the potential for speeding up an offline handwritten word recognition system via concurrency. The goal of the system is to achieve both full accuracy and high speed when taking into account large vocabularies. This was accomplished by integrating the recognition process with multiprocessing and distributed computing concepts. Experimental results showed that the multiprocessing environment is very promising in enhancing a sequential offline handwritten word recognition system performance
Keywords :
feature extraction; handwritten character recognition; image segmentation; multiprocessing systems; parallel programming; vocabulary; word processing; concurrency; distributed computing; distributed scheme; large vocabularies; large vocabulary problems; lexicon-driven handwritten word recognition; multiprocessing; multiprocessing environment; offline handwritten word recognition systems; recognition process; recognition rates; sequential offline handwritten word recognition; speed factor; Computer architecture; Concurrent computing; Decoding; Distributed computing; Feature extraction; Handwriting recognition; Hidden Markov models; Image segmentation; Pattern recognition; Vocabulary;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Document Analysis and Recognition, 2001. Proceedings. Sixth International Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7695-1263-1
Type :
conf
DOI :
10.1109/ICDAR.2001.953872
Filename :
953872
Link To Document :
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