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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Fang, C. Hull, J.J. |
| Copyright Year | 1995 |
| Description | Author affiliation: CEDAR, State Univ. of New York, Buffalo, NY, USA (Fang, C.) |
| Abstract | An hypothesis testing approach for recognizing machine-printed words is presented in this paper. Based on knowledge of the document font and candidates for the identity of a word, this approach searches a tree of word decisions to generate and test hypotheses for character recognition and segmentation. The search starts at each sequential character position from both ends of a word image and proceeds inward. The accumulated cost of reaching a certain partial recognition decision is combined with the estimate of the potential cost to reach a goal state using an A* search algorithm. The proposed algorithm compensates for local degradations by relying on global characteristics of a word image. Tests of the algorithm show a recognition rate of 98.93% on degraded scanned document images with touching characters. |
| Starting Page | 360 |
| Ending Page | 363 |
| File Size | 360674 |
| Page Count | 4 |
| File Format | |
| ISBN | 0818671289 |
| DOI | 10.1109/ICDAR.1995.599013 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1995-08-14 |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Testing Degradation Character recognition Costs Image segmentation Algorithm design and analysis State estimation Optical character recognition software Shape Sequential analysis |
| Content Type | Text |
| Resource Type | Article |
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