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A Genetic Algorithm Search for Improved Halftone Masks

Summary: A Genetic Algorithm Search for Improved
Halftone Masks
Peter G. Anderson1
, Jonathan S. Arney, Samuel A. Inverso, Daniel R. Kunkle,
Timothy M. Lebo, and Chadd Merrigan
Laboratory for Applied Computing, Rochester Institute of Technology
Rochester, New York, USA
We present a genetic algorithm that automatically gen-
erates halftone masks optimized for use in specific print-
ing systems. The search is guided by a single figure of
merit based on a detailed model of the printing process and
the human visual system. Our experiments show that ge-
netic 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 en-
hance the performance of the GA.
1. Introduction
Techniques for rendering excellent black and white ap-
proximations of grayscale images, called digital halfton-


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


Collections: Computer Technologies and Information Sciences