DocumentCode :
1581568
Title :
A two-stage HMM-based system for recognizing handwritten numeral strings
Author :
Britto, A. ; Sabourin, Robert ; Bortolozzi, Flavio ; Suen, Ching Y.
Author_Institution :
Pontificia Univ. Catolica do Parana, Curitiba, Brazil
fYear :
2001
fDate :
6/23/1905 12:00:00 AM
Firstpage :
396
Lastpage :
400
Abstract :
The authors propose a handwritten numeral string recognition method composed of two HMM-based stages. The first stage uses an implicit segmentation strategy based on string contextual information to provide multiple segmentation-recognition paths. These paths are verified and re-ranked by using a verification stage based on a digit classifier. It allows the use of two sets of features and numeral models: one taking into account both segmentation and recognition aspects in an implicit segmentation based strategy, and another considering just recognition aspects of isolated digits. The two system stages are shown to be complementary in the sense that the verification stage is shown to be a promising idea to deal with the loss in terms of recognition performance brought about by the necessary tradeoff between segmentation and recognition carried out in the first system stage
Keywords :
formal verification; handwritten character recognition; hidden Markov models; image segmentation; string matching; HMM-based stages; digit classifier; handwritten numeral string recognition; implicit segmentation based strategy; implicit segmentation strategy; isolated digits; multiple segmentation-recognition paths; numeral models; recognition aspects; recognition performance; string contextual information; two-stage HMM-based system; verification stage; Assembly; Data mining; Dynamic programming; Feature extraction; Handwriting recognition; Hidden Markov models; Image segmentation; Machine intelligence; Pattern recognition; Performance loss;
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.2001.953820
Filename :
953820
Link To Document :
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