Systematic bias in OCR experiments
Daniel Lopresti, Andrew Tomkins, Jiangying Zhou · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1995
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.