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Proceedings Paper

Systematic bias in OCR experiments
Author(s): Daniel P. Lopresti; Andrew Tomkins; Jiangying Zhou
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Paper Abstract

In this paper, we examine the effects of systematic differences (bias) and sample size (variance) on computed OCR accuracy. We present results from large-scale experiments simulating several groups of researchers attempting to perform the same test, but using slightly different equipment and procedures. We first demonstrate that seemingly minor systematic differences between experiments can result in significant biases in the computed OCR accuracy. Then we show that while a relatively small number of pages is sufficient to obtain a precise estimate of accuracy in the case of `clean' input, real-world degradation can greatly increase the required sample size.

Paper Details

Date Published: 30 March 1995
PDF: 9 pages
Proc. SPIE 2422, Document Recognition II, (30 March 1995); doi: 10.1117/12.205822
Show Author Affiliations
Daniel P. Lopresti, Panasonic Technologies, Inc. (United States)
Andrew Tomkins, Panasonic Technologies, Inc. (United States)
Jiangying Zhou, Panasonic Technologies, Inc. (United States)


Published in SPIE Proceedings Vol. 2422:
Document Recognition II
Luc M. Vincent; Henry S. Baird, Editor(s)

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