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Related Experiment Video

Updated: Mar 25, 2026

Author Spotlight: Quantitative Characterization of Liquid Photosensitive Bioink Properties for Continuous Digital Light Processing Based Printing
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Modeling coverage-dependent ink thickness in ink-jet printing.

Ludovic G Coppel, Radovan Slavuj, Jon Yngve Hardeberg

    Applied Optics
    |February 25, 2016
    PubMed
    Summary

    We improved the Murray-Davis halftone model to predict ink dot reflectance changes from ink spreading. This enhanced model offers greater accuracy for various printers and paper types, aiding faster printer calibration.

    Area of Science:

    • Color science
    • Print technology
    • Image reproduction

    Background:

    • The Murray-Davis model is widely used for predicting halftone reflectance.
    • Ink spreading significantly affects ink dot reflectance and print accuracy.
    • Existing models like Yule-Nielsen and Clapper-Yule have limitations in predicting these effects.

    Purpose of the Study:

    • To extend the Murray-Davis halftone reflectance model to incorporate ink spreading effects.
    • To improve the prediction accuracy of halftone reflectance models.
    • To provide a better understanding of reflectance from halftone prints for printer calibration.

    Main Methods:

    • A simple extension to the Murray-Davis model was proposed.
    • The extended model accounts for changes in ink dot reflectance due to ink spreading.

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  • Model performance was evaluated against classical Yule-Nielsen and Clapper-Yule models.
  • Main Results:

    • The extended Murray-Davis model showed significant improvement in prediction accuracy.
    • Accuracy improvements were observed across various paper substrates and printer combinations.
    • Ink dot thickness dependency was identified as a key limitation of the original Murray-Davis model.
    • Optical dot gain can be neglected if the model is calibrated for a specific printer, ink, and substrate.

    Conclusions:

    • The proposed extension enhances the accuracy of halftone reflectance prediction.
    • The model offers a more robust understanding of reflectance from halftone prints.
    • This work contributes to the development of more efficient and accurate physical models for printer calibration.