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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Matan, O. Baird, H.S. Bromley, J. Burges, C.J.C. Denker, J.S. Jackel, L.D. Le Cun, Y. Pednault, E.P.D. Satterfield, W.D. Stenard, C.E. Thompson, T.J. |
| Copyright Year | 1970 |
| Abstract | A neural network algorithm-based system that reads handwritten ZIP codes appearing on real US mail is described. The system uses a recognition-based segmenter, that is a hybrid of connected-components analysis (CCA), vertical cuts, and a neural network recognizer. Connected components that are single digits are handled by CCA. CCs that are combined or dissected digits are handled by the vertical-cut segmenter. The four main stages of processing are preprocessing, in which noise is removed and the digits are deslanted, CCA segmentation and recognition, vertical-cut-point estimation and segmentation, and directly lookup. The system was trained and tested on approximately 10000 images, five- and nine-digit ZIP code fields taken from real mail.< |
| Sponsorship | IEEE Computer Society |
| Starting Page | 59 |
| Ending Page | 63 |
| Page Count | 5 |
| File Size | 559509 |
| File Format | |
| ISSN | 00189162 |
| Volume Number | 25 |
| Issue Number | 7 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1992-07-01 |
| Publisher Place | U.S.A. |
| Access Restriction | One Nation One Subscription (ONOS) |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Handwriting recognition Pattern recognition Research and development Image processing Laboratories Character recognition Image recognition Information systems Man machine systems Robustness |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Science |
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