Printer model and least-squares halftoning using genetic algorithms

Chih Ching Lai, Din Chang Tseng

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


In this paper, a least-square model-based halftoning technique using a genetic algorithm is proposed to produce a halftone image by minimizing the perceived reflectance difference between the halftone image and its original image. We use a least-square criterion incorporating with the property of the human visual system to measure the difference between the two images. The genetic algorithm is used for investigating the complicated search problem. The standard halftoning techniques, such as error diffusion and least-square halftoning, produce gray-level distortion because of dot-gain problem. In this study, we use a modified dot-overlap printer model to compensate the gray-level distortion. The printer model combines with a measurement-based algorithm to estimate the print-dot radius and makes the proposed halftoning approach adapted to a wide variety of printers and papers. Experiments show that the proposed approach produces more accurate gray levels than several common-used halftoning methods produce.

Original languageEnglish
Pages (from-to)241-249
Number of pages9
JournalJournal of Imaging Science and Technology
Issue number3
StatePublished - May 1998


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