Testing imaging systems with genetic algorithms - case: error diffusion methods

Timo Mantere

doi:10.1117/12.752590

10 September 2007 Testing imaging systems with genetic algorithms - case: error diffusion methods

Timo Mantere

Proceedings Volume 6764, Intelligent Robots and Computer Vision XXV: Algorithms, Techniques, and Active Vision; 67640V (2007) https://doi.org/10.1117/12.752590
Event: Optics East, 2007, Boston, MA, United States

Abstract

This paper studies the testing of the imaging systems and algorithms with the genetic algorithms. We test if there are inherent natural weaknesses in the image processing algorithm or system and can they are search and found with the evolutionary algorithms. In this paper, we test the weaknesses of the error diffusion halftoning methods. We also take a closer look at the method and identify why these weaknesses appear and are relatively easy to identify with synthetic test images. Moreover, we discuss the importance of comprehensive testing before the results with some image processing methods can be trustworthy. The results seem to suggest that the error diffusion methods do not have as apparent inherent problems as e.g. dispersed dot method, but the GA testing does reveal some other problems, like delayed response to the image tone changes. The different error diffusion methods have similar problems, but with different intensity.

Citation Download Citation

Timo Mantere "Testing imaging systems with genetic algorithms - case: error diffusion methods", Proc. SPIE 6764, Intelligent Robots and Computer Vision XXV: Algorithms, Techniques, and Active Vision, 67640V (10 September 2007); https://doi.org/10.1117/12.752590

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