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Automatic correlation and calibration of noisy sensor readings using elite genetic algorithms

✍ Scribed by R.R. Brooks; S.S. Iyengar; J. Chen


Book ID
102989477
Publisher
Elsevier Science
Year
1996
Tongue
English
Weight
996 KB
Volume
84
Category
Article
ISSN
0004-3702

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✦ Synopsis


This paper explores an image processing application of optimization techniques which entails interpreting noisy sensor data. The application is a generalization of image correlation; we attempt to find the optimal gruence which matches two overlapping gray scale images corrupted with noise.

Both tabu search and genetic algorithms are used to find the parameters which match the two images. A genetic algorithm approach using an elitist reproduction scheme is found to provide significantly superior results.