Abstract
In this paper, we describe a new 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.
| Original language | English |
|---|---|
| Pages (from-to) | 172-188 |
| Number of pages | 17 |
| Journal | IEEE Transactions on Pattern Analysis and Machine Intelligence |
| Volume | 24 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 1 Feb 2002 |
| Externally published | Yes |
Keywords
- Handwriting recognition
- Hidden Markov models
- Phrase detection and recognition
- Statistical modeling
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