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Proceedings Paper

Testing imaging systems with genetic algorithms - case: error diffusion methods
Author(s): Timo Mantere
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Paper 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.

Paper Details

Date Published: 10 September 2007
PDF: 12 pages
Proc. SPIE 6764, Intelligent Robots and Computer Vision XXV: Algorithms, Techniques, and Active Vision, 67640V (10 September 2007); doi: 10.1117/12.752590
Show Author Affiliations
Timo Mantere, Univ. of Vaasa (Finland)

Published in SPIE Proceedings Vol. 6764:
Intelligent Robots and Computer Vision XXV: Algorithms, Techniques, and Active Vision
David P. Casasent; Ernest L. Hall; Juha Röning, Editor(s)

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