Abstract
Emergency health care facilities lack automated medical form recognition systems necessary for efficient epidemiological and health surveillance analysis. The task is to extract handwritten text from the New York State (NYS) Pre-Hospital Care Report (PCR) and determine its ASCII translation. Our approach hybridizes image processing and semantic lexicon pruning to compensate for the otherwise enormous lexicon size. In this paper we expand on our IEEE CBMS 2001 paper, which provided a conceptual overview, by probing into our recognizer design and performance measurements.
| Original language | English |
|---|---|
| Pages (from-to) | 428-433 |
| Number of pages | 6 |
| Journal | Proceedings of the IEEE Symposium on Computer-Based Medical Systems |
| Volume | 17 |
| State | Published - 2004 |
| Event | Proceedings 17th IEEE Symposium on Computer-Based Medical Systems, CBMS 2004 - Bethesda, MD, United States Duration: Jun 24 2004 → Jun 25 2004 |
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