Recognition of Handprinted Digits
| Type of publication: | Idiap-RR |
| Citation: | breuel-93.02 |
| Number: | Idiap-RR-06-1993 |
| Year: | 1993 |
| Institution: | IDIAP |
| Abstract: | This paper describes a system that recognizes hand-printed digits. The system is based on optimal bounded error matching, a technique already in common use in general-purpose 2D and 3D visual object recognition systems in cluttered, noisy scenes. In this paper, we demonstrate that the same techniques achieve high recognition rates (up to 99.2\%) on real-world data (the NIST database of hand-printed census forms and the CEDAR database of digits extracted from U.S. mail ZIP codes). As part of the system, we describe a post-processing step for $k$-nearest neighbor classifiers based on decision trees that can be used (in place of the usual heuristic methods) for setting thresholds and improves recognition rates significantly. |
| Userfields: | ipdmembership={vision}, |
| Keywords: | |
| Projects |
Idiap |
| Authors | |
| Added by: | [UNK] |
| Total mark: | 0 |
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