Name
Abstract | ||
|---|---|---|
This article describes a system being developed to process bank checks. To interpret the various items of information contained in the image of a check, many modules are required. These begin with the implementation of image-processing techniques to isolate and identify each category of handwritten information. The relevant recognizers are then used to read the numeric and legal amounts, as well as the date on the check. The recognizers must be able to process digits (in isolated or connected form), handwritten cursive words, and a mixture of numerals and words, the last of which is necessary for the recognition of the date written on checks. While these recognizers have different functions, they can also share certain components. We describe the algorithms used in the implementation of each module, their experimental results, and some connections among the modules. (C) 1996 John Wiley & Sons, Inc. |
Year | DOI | Venue |
|---|---|---|
1996 | 10.1002/(SICI)1098-1098(199624)7:4<392::AID-IMA14>3.0.CO;2-Y | INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY |
Field | DocType | Volume |
Cashier's check,Computer science,Artificial intelligence,Machine learning | Journal | 7 |
Issue | ISSN | Citations |
4 | 0899-9457 | 29 |
PageRank | References | Authors |
2.50 | 0 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ching Y. Suen | 1 | 7569 | 1127.54 |
| Louisa Lam | 2 | 29 | 2.50 |
| Didier Guillevic | 3 | 97 | 10.70 |
| Nick W. Strathy | 4 | 29 | 2.50 |
| Mohamed Cheriet | 5 | 2047 | 238.58 |
| Joseph N. Said | 6 | 170 | 36.40 |
| Rong Fan | 7 | 29 | 2.50 |