Abstract
The purpose of this paper is to describe the computational algorithmic generation of high-quality colour patterns (digital halftones). At the beginning, the formal model for generation of the digital halftones, the so-called grey pattern problem (GPP) is introduced. Then, the heuristic algorithm for the solution of the grey pattern problem is discussed. Although the algorithm employed does not guarantee the optimality of the solutions found, still perfect quality, near-optimal (and in some cases probably optimal) solutions can be achieved within reasonable computation time. Further, we provide the preliminary results of the extensive computational experiments with the extra-large instance (data set) of the GPP. As a confirmation of the quality of the analytical solutions produced, we also give the visual representations of fine-looking graphic halftone patterns.
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References
Burkard, R.E., Karisch, S., Rendl, F.: QAPLIB – a quadratic assignment problem library. J. Glob. Optim. 10, 391–403 (1997), http://www.seas.upenn.edu/qaplib (cited June 29, 2013)
Çela, E.: The Quadratic Assignment Problem: Theory and Algorithms. Kluwer, Dordrecht (1998)
Drezner, Z.: Finding a cluster of points and the grey pattern quadratic assignment problem. OR Spectrum 28, 417–436 (2006)
Kang, H.R.: Digital Color Halftoning. In: Dougherty, E.R. (ed.). SPIE/IEEE Series on Imaging Science & Engineering. The SPIE Optical Engineering Press/IEEE Press, Bellingham/Piscataway (1999)
Lau, D.L., Arce, G.R.: Modern Digital Halftoning, Sec. Ed. In: Liu, K.J.R. (ed.). Signal Processing and Communications Series. Marcel Dekker, New York-Basel (2008)
Misevičius, A.: Experiments with hybrid genetic algorithm for the grey pattern problem. Informatica 17, 237–258 (2006)
Misevičius, A.: Generation of grey patterns using an improved genetic evolutionary algorithm: Some new results. Inform. Technol. Contr. 40, 330–343 (2011)
Misevicius, A.: An implementation of the iterated tabu search algorithm for the quadratic assignment problem. OR Spectrum 34, 665–690 (2012), doi:10.1007/s00291-011-0274-z
Misevičius, A., Rubliauskas, D.: Performance of hybrid genetic algorithm for the grey pattern problem. Inform. Technol. Contr. 34, 15–24 (2005)
Sivanandam, S.N., Deepa, S.N.: Introduction to Genetic Algorithms. Springer, Heidelberg (2008)
Taillard, E.D.: Comparison of iterative searches for the quadratic assignment problem. Locat. Sci. 3, 87–105 (1995)
Taillard, E.D., Gambardella, L.M.: Adaptive memories for the quadratic assignment problem. Techn. Report. IDSIA-87-97, Lugano, Switzerland (1997)
Ulichney, R.A.: Digital Halftoning. MIT Press, London (1987)
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Misevičius, A., Guogis, E., Stanevičienė, E. (2013). Computational Algorithmic Generation of High-Quality Colour Patterns. In: Skersys, T., Butleris, R., Butkiene, R. (eds) Information and Software Technologies. ICIST 2013. Communications in Computer and Information Science, vol 403. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41947-8_24
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DOI: https://doi.org/10.1007/978-3-642-41947-8_24
Publisher Name: Springer, Berlin, Heidelberg
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