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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Madhvanath, S. Govindaraju, V. Ramanaprasad, V. Lee, D.S. Srihari, S.N. |
| Copyright Year | 1995 |
| Description | Author affiliation: Center of Excellence for Document Anal. & Recognition, State Univ. of New York, Buffalo, NY, USA (Madhvanath, S.) |
| Abstract | Commercial forms-reading systems for extraction of data from forms do not meet acceptable accuracy requirements on forms filled out by hand. In December 1993, NIST called industry and research organizations working in the area of handwriting recognition to participate in a test to determine the state of the art in the area. A database of form images containing actual responses received by the US Census Bureau was provided. The handwritten responses are very loosely constrained in terms of writing style, format of response and choice of text. The sizes of the lexicons provided are very large (about 50000 entries) and yet the coverage is incomplete (about 70%). In this paper we discuss the approach taken by CEDAR to automate the task of reading the census forms. The subtasks of field extraction and phrase recognition are described. |
| Starting Page | 82 |
| Ending Page | 85 |
| File Size | 428022 |
| Page Count | 4 |
| File Format | |
| ISBN | 0818671289 |
| DOI | 10.1109/ICDAR.1995.598949 |
| 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 | Data mining Handwriting recognition Writing NIST Image recognition System testing Text recognition Text analysis Image databases Automatic testing |
| Content Type | Text |
| Resource Type | Article |
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