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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Adnan El-Nasan Veeramachaneni, Sriharsha Nagy, G. |
| Copyright Year | 2003 |
| Description | Author affiliation: Rensselaer Polytech. Univ., Troy, NY, USA (Adnan El-Nasan; Sriharsha Veeramachaneni; Nagy, G.) |
| Abstract | We propose further improvement of a handwriting recognition method that avoids segmentation while able to recognize words that were never seen before in handwritten form. This method is based on the fact that few pairs of English words share exactly the same set of letter bigrams and even fewer share longer n-grams. The lexical n-gram matches between every word in a lexicon and a set of reference words can be precomputed. A position-based match function then detects the matches between the handwritten signal of a query word and each reference word. We show that with a reasonable set of reference words, the recognition of lexicon words exceeds 90%. |
| Sponsorship | TC10 (Graphics Recognition) and TC11 (Reading Syst.) of the Int. Assoc. Pattern Recognition (IAPR) |
| Starting Page | 577 |
| Ending Page | 582 |
| File Size | 542045 |
| Page Count | 6 |
| File Format | |
| ISBN | 0769519601 |
| DOI | 10.1109/ICDAR.2003.1227730 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2003-08-06 |
| Publisher Place | UK |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Handwriting recognition Character recognition Pattern matching Vocabulary Computer vision Hidden Markov models Signal processing Error correction codes Error correction Optical character recognition software |
| Content Type | Text |
| Resource Type | Article |
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