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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Koerich, Alessandro L. Sabourin, Robert Suen, Ching Y. |
| Copyright Year | 2002 |
| Description | Author affiliation: Centre for Pattern Recognition and Machine Intelligence, Concordia University, Montréal, H3G 1M8, Canada (Suen, Ching Y.) || Lab. d'Imagerie, de Vision et d'Intelligence Artificielle, École de Technologie Supérieure, Montréal, H3C 1K3, Canada (Koerich, Alessandro L.; Sabourin, Robert) |
| Abstract | This paper describes a fast two-level Viterbi search algorithm for recognizing handwritten words as a sequence of characters concatenated according to a lexicon. The algorithm is based on hidden Markov model (HMM) representations of characters and it breaks up the computation of word likelihood scores into two levels: state level and character level. This enables the reuse of likelihood scores of characters to decode all words in the lexicon, avoiding repeated computation of state sequences. Experimental results with an 85,000-word vocabulary indicate that the computational cost of an off-line handwritten word recognition system may be reduced by more than a factor of 20 while not introducing search errors. |
| File Size | 579086 |
| File Format | |
| ISBN | 0780374029 |
| ISSN | 15206149 |
| DOI | 10.1109/ICASSP.2002.5745418 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2002-05-13 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Handwriting recognition |
| Content Type | Text |
| Resource Type | Article |
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