DocumentCode :
1560324
Title :
A statistical approach for phrase location and recognition within a text line: an application to street name recognition
Author :
El-Yacoubi, Mounim A. ; Gilloux, Michel ; Bertille, Jean-Michel
Volume :
24
Issue :
2
fYear :
2002
fDate :
2/1/2002 12:00:00 AM
Firstpage :
172
Lastpage :
188
Abstract :
We describe an approach to conjointly locate and recognize a street name within a street line. The system developed is based on a probabilistic framework that naturally integrates various knowledge sources to emit a final decision. At the handwriting signal level, hidden Markov models are extensively used to provide the needed matching scores. Several optimization techniques are employed to speed up the processing time. Experiments carried out on large data sets of street line images, automatically extracted from real French mail envelope images, show very promising results
Keywords :
feature extraction; handwritten character recognition; hidden Markov models; image segmentation; probability; French mail envelope images; handwriting recognition; handwritten character recognition; hidden Markov models; matching scores; phrase location; phrase recognition; probabilistic framework; statistical approach; street name recognition; text line; Data mining; Error analysis; Focusing; Handwriting recognition; Hidden Markov models; Image recognition; Postal services; Sorting; Text recognition; Writing;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/34.982898
Filename :
982898
Link To Document :
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