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Good Halftone Masks via Genetic Algorithms Peter G. Anderson, Jonathan S. Arney, Samuel A. Inverso, Daniel R. Kunkle,
 

Summary: Good Halftone Masks via Genetic Algorithms
Peter G. Anderson, Jonathan S. Arney, Samuel A. Inverso, Daniel R. Kunkle,
Timothy M. Lebo, and Chadd Merrigan
Laboratory for Applied Computing, RIT, Rochester, NY
Abstract
We present a genetic algorithm that automatically
generates halftone masks optimized for use in
specific printing systems. The search is guided
by a single figure of merit based on a model of
the printing process and the human visual sys-
tem.
Our experiments show that genetic algorithms
are effective in finding improved halftone masks
and that two methods of reducing the search space
to particular subsets of possible halftone masks
greatly enhance the search performance.12
Genetic Algorithms
A genetic algorithm (GA) mimics evolutionary
processes­i.e., selective breeding­to find good so-
lutions to hard problems indirectly. A GA works

  

Source: Anderson, Peter G. - Department of Computer Science, Rochester Institute of Technology

 

Collections: Computer Technologies and Information Sciences