Threshold matrix for digital halftoning by genetic algorithm optimization

Jarmo T. Alander; Timo J. Mantere; Tero Pyylampi

doi:10.1117/12.325765

6 October 1998 Threshold matrix for digital halftoning by genetic algorithm optimization

Jarmo T. Alander, Timo J. Mantere, Tero Pyylampi

Proceedings Volume 3522, Intelligent Robots and Computer Vision XVII: Algorithms, Techniques, and Active Vision; (1998) https://doi.org/10.1117/12.325765
Event: Photonics East (ISAM, VVDC, IEMB), 1998, Boston, MA, United States

Abstract

Digital halftoning is used both in low and high resolution high quality printing technologies. Our method is designed to be mainly used for low resolution ink jet marking machines to produce both gray tone and color images. The main problem with digital halftoning is pink noise caused by the human eye's visual transfer function. To compensate for this the random dot patterns used are optimized to contain more blue than pink noise. Several such dot pattern generator threshold matrices have been created automatically by using genetic algorithm optimization, a non-deterministic global optimization method imitating natural evolution and genetics. A hybrid of genetic algorithm with a search method based on local backtracking was developed together with several fitness functions evaluating dot patterns for rectangular grids. By modifying the fitness function, a family of dot generators results, each with its particular statistical features. Several versions of genetic algorithms, backtracking and fitness functions were tested to find a reasonable combination. The generated threshold matrices have been tested by simulating a set of test images using the Khoros image processing system. Even though the work was focused on developing low resolution marking technology, the resulting family of dot generators can be applied also in other halftoning application areas including high resolution printing technology.

Citation Download Citation

Jarmo T. Alander, Timo J. Mantere, and Tero Pyylampi "Threshold matrix for digital halftoning by genetic algorithm optimization", Proc. SPIE 3522, Intelligent Robots and Computer Vision XVII: Algorithms, Techniques, and Active Vision, (6 October 1998); https://doi.org/10.1117/12.325765

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