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Proceedings Paper

Accuracy of image matching by pixelwise and zonal classifiers
Author(s): V. V. Savelyev; A. S. Pletnev
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Paper Abstract

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.

Paper Details

Date Published: 1 November 1993
PDF: 6 pages
Proc. SPIE 2111, Symposium on Russian Airborne Geophysics and Remote Sensing, (1 November 1993); doi: 10.1117/12.162860
Show Author Affiliations
V. V. Savelyev, Institute of Precise Instruments (Russia)
A. S. Pletnev, Institute of Precise Instruments (Russia)


Published in SPIE Proceedings Vol. 2111:
Symposium on Russian Airborne Geophysics and Remote Sensing
Norman Harthill, Editor(s)

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