Accuracy of image matching by pixelwise and zonal classifiers
Vladimir V. Savelyev, A. S. Pletnev · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1993
The problem of digital image recognition can be regarded both as a problem of testing multiple hypotheses and as a position measurement problem. In the first case, a criterion of algorithm efficiency can be the probability of a correct decision, while in the second one it should be the measurement accuracy [1]. Automatic image recognition can result in so-called anomalous errors when the maximum of the algorithm response (which we shall call the decision function, or DF) appears at a location entirely different from the true position. Usually, the response field has a peak at approximately the correct place and a number of other, smaller peaks located at random. Under strong image distortions, one of these false peaks can become larger than the main peak, leading to an anomalous error. On the other hand, the maximum of the main peak may be somewhat shifted from the correct match position. This deviation, usually small, will be referred to as a normal error.