Genetic programming applied to automatic algorithm design in multi-scale inspection systems

Avinash Burla; Tobias Haist; Wolfram Lyda; Wolfgang Osten

doi:10.1117/1.OE.51.6.067001

5 June 2012 Genetic programming applied to automatic algorithm design in multi-scale inspection systems

Avinash Burla, Tobias Haist, Wolfram Lyda, Wolfgang Osten

Author Affiliations +

Optical Engineering, Vol. 51, Issue 6, 067001 (June 2012). https://doi.org/10.1117/1.OE.51.6.067001

Abstract

In recent years image-processing has become a central part of optical inspection and measurement systems. Typically, after measuring the given specimen by utilizing a suitable sensor, image-processing algorithms are used to detect dedicated features such as surface defects. These algorithms are usually designed, optimized, and tested by an image-processing expert according to the task specifications. A methodology (based on genetic programming) is presented to automatically generate, optimize, and test such algorithms without the necessity of an image-processing expert. We also present several examples of inspection tasks to support the concept. For efficiency, an automated multi-scale multi-sensor inspection strategy is employed.

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Avinash Burla, Tobias Haist, Wolfram Lyda, and Wolfgang Osten "Genetic programming applied to automatic algorithm design in multi-scale inspection systems," Optical Engineering 51(6), 067001 (5 June 2012). https://doi.org/10.1117/1.OE.51.6.067001

Published: 5 June 2012

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