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Abstract: This paper presents an image halftoning algorithm with a reaction-diffusion system in which periodic patterns called Turing patterns autonomously emerge. Image halftoning refers to conversion of a gray level image to a binary image so that the human visual system can perceive the original gray level image from the converted binary one. The reaction-diffusion system has activator and inhibitor distributions, and creates the Turing type periodic patterns in the distributions from an initial noisy distributions under the condition of long-range inhibition. Characteristics of the Turing patterns depend on a parameter of the reaction-diffusion system. Thus, by modulating the parameter distribution according to an image brightness distribution, the proposed algorithm creates Turing patterns of which characteristics distribute spatially; the human visual system can perceive distribution of the Turing patterns as the original image. Application of the proposed algorithm to a test image demonstrates its qualitative performance and convergence.(More)

This paper presents an image halftoning algorithm with a reaction-diffusion system in which periodic patterns called Turing patterns autonomously emerge. Image halftoning refers to conversion of a gray level image to a binary image so that the human visual system can perceive the original gray level image from the converted binary one. The reaction-diffusion system has activator and inhibitor distributions, and creates the Turing type periodic patterns in the distributions from an initial noisy distributions under the condition of long-range inhibition. Characteristics of the Turing patterns depend on a parameter of the reaction-diffusion system. Thus, by modulating the parameter distribution according to an image brightness distribution, the proposed algorithm creates Turing patterns of which characteristics distribute spatially; the human visual system can perceive distribution of the Turing patterns as the original image. Application of the proposed algorithm to a test image demonstrates its qualitative performance and convergence.

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Nomura, A. (2012). Image Halftoning with Turing Patterns.In Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: ECTA, (IJCCI 2012) ISBN 978-989-8565-33-4, pages 286-289. DOI: 10.5220/0004149202860289

@conference{ecta12, author={Atsushi Nomura.}, title={Image Halftoning with Turing Patterns}, booktitle={Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: ECTA, (IJCCI 2012)}, year={2012}, pages={286-289}, publisher={SciTePress}, organization={INSTICC}, doi={10.5220/0004149202860289}, isbn={978-989-8565-33-4}, }

TY - CONF

JO - Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: ECTA, (IJCCI 2012) TI - Image Halftoning with Turing Patterns SN - 978-989-8565-33-4 AU - Nomura, A. PY - 2012 SP - 286 EP - 289 DO - 10.5220/0004149202860289