Least-squares color Halftoning Algorithm Based on Clustering Analysis

DOI

10.2991/isrme-15.2015.282How to use a DOI?

Keywords

Color halftoning;Human vision system(HVS);Printer model;Clustering Analysis;Least squares

Abstract

We presents a new method for color printers. Our algorithm applies to both a color printer model and a model for the human visual system (HVS). The method strives to minimize the perceived error between the continuous original image and the halftone image. The color printer models can account for a variety of printer characteristics. We propose a specific printer model that accounts for overlap between neighboring dots of ink and spectral absorption properties of the inks. The color image is partitioned into several regions using clustering segmentation method, whose performance depends on the selection of distance metrics. Each clustering uses the least-squares model-based(Lsmb) algorithm to obtain halftone image. A performance measure for halftone images is used to evaluate our algorithm. Analysis and simulation results show that the proposed algorithm produces better color halftone image quality when we increase the number of clustering with a certain range.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Zifen He
AU  - Yinhui Zhang
PY  - 2015/04
DA  - 2015/04
TI  - Least-squares color Halftoning Algorithm Based on Clustering Analysis
BT  - Proceedings of the 2015 International Conference on Intelligent Systems Research and Mechatronics Engineering
PB  - Atlantis Press
SP  - 1411
EP  - 1414
SN  - 1951-6851
UR  - https://doi.org/10.2991/isrme-15.2015.282
DO  - 10.2991/isrme-15.2015.282
ID  - He2015/04
ER  -