Bibtex entry:

@inproceedings{icdar:kovacs97,
  key  ={icdar:kovacs97},
  year="1997",
  title={Confidence Computation Improvement in an Optical Field Reading System},
  author={A. Benedetti and Zs. M. Kovacs-V.},
  booktitle={Proc. of ICDAR'97 Ulm - Germany},
  keywords={OCR image confidence}, 
  abstract={An expression in closed form is derived for the recognition
error vs. rejection rate of optical character or word recognition
systems. This expression explains,for the first time, the qualitative
relationship between the raw error rate at zero reject and the
behavior of error vs. rejection curves of several isolated character
classifiers.  It also allows to define a lower bound for the error
rate of any recognition system employing a rejection process based on
the definition of a confidence threshold.This relation has also proved
to be useful to make a quantitative comparison between two confidence
computation methods implemented in a system for reading USA Census '90
hand-written forms. The newly proposed method is based upon a
confidence model integrating single character confidence levels,
digram statistics and other information from the dictionary matching
phase. Two implementations of this methodology have been investigated:
the first is a linear model, the second is a multi-layer
perceptron. Experimental results on the NIST Special Database 12 and
13 have not shown a clear advantage of the connectionist model over
the simple linear model. At a $50\%$ rejection rate, the field error
rate calculated using the new confidence computation algorithm
decreased from $47.7\%$ to $44.6\%$, which represents a considerable
improvement, given a theoretical lower bound of $40.8\%$ on the error
rate.}, 
}

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