Systematic bias in OCR experiments

Daniel P. Lopresti; Andrew Tomkins; Jiangying Zhou

doi:10.1117/12.205822

30 March 1995 Systematic bias in OCR experiments

Daniel P. Lopresti, Andrew Tomkins, Jiangying Zhou

Proceedings Volume 2422, Document Recognition II; (1995) https://doi.org/10.1117/12.205822
Event: IS&T/SPIE's Symposium on Electronic Imaging: Science and Technology, 1995, San Jose, CA, United States

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.

Citation Download Citation

Daniel P. Lopresti, Andrew Tomkins, and Jiangying Zhou "Systematic bias in OCR experiments", Proc. SPIE 2422, Document Recognition II, (30 March 1995); https://doi.org/10.1117/12.205822

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