Deducing Ink Spreading Curves from Reflection Spectra Acquired Within Printed Color Images

Hersch, Roger D.; Brichon, Mathieu; Bugnon, Thomas; Hébert, Mathieu

doi:10.2352/j.imagingsci.technol.2009.53.3.030502

Cited by 7 publications

(3 citation statements)

References 13 publications

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“…As seen in previous works, we should use uniform image tiles to calibrate the IS‐YNSN model. The algorithm used in this contribution to extract such uniform tiles from color images is similar to the optimized selection algorithm described in Ref.…”

Section: Selection Of Image Calibration Tilesmentioning

confidence: 99%

“…Instead of calibrating the IS‐YNSN model with predetermined color‐constant patches, we propose a calibration procedure relying on the measurements of image tiles extracted from printed color images. In previous contributions of the present authors, the content of printed color images has already been used for the calibration of ink spreading, but not for the YNSN model itself, that is, the Neugebauer primaries still had to be measured and the Yule‐Nielsen n‐ value determined. Balasubramanian proposed to recalibrate the Neugebauer primaries based on a training set of measured samples, but only as an optimization step based on initially measured primary reflectances…”

Section: Introductionmentioning

confidence: 99%

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Recovering neugebauer colorant reflectances and Ink‐spreading curves from printed color images

Bugnon

Hersch

2013

Color Research & Application

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Spectral reflection prediction models, although effective, are impractical for certain industrial applications such as self-calibrating devices and online monitoring because their calibration requires specific color-constant calibration patches. Using the CMYK Ink Spreading enhanced Yule-Nielsen modified Spectral Neugebauer model (IS-YNSN), we propose a method to recover the colorant reflectances (Neugebauer primaries), the ink spreading curves, and the Yule-Nielsen n-value using only tiles extracted from printed color images. There is no prior knowledge about the reproduction device. Thanks to a set of constraints based on Principal Component Analysis (PCA) and the relationships between composed Neugebauer primaries and the ink transmittances, good approximations of the Neugebauer primaries are achieved. These approximations are then optimized, yielding an accurately calibrated IS-YNSN model comparable to one obtained by classical calibrations. A detailed analysis of these calibrations shows that 25 well-chosen CMYK image calibration tiles are sufficient to accurately recover both the Neugebauer primaries and the ink spreading curves.

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Section: Selection Of Image Calibration Tilesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Recovering neugebauer colorant reflectances and Ink‐spreading curves from printed color images

Bugnon

Hersch

2013

Color Research & Application

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“…They are extracted from a color image and used to perform the model calibration, as mentioned in previous publications of the authors. These publications describe an algorithm to automatically select image tiles 8 and use them to calibrate the ink spreading model [8][9] .…”

Section: Introductionmentioning

confidence: 99%

Calibrating ink spreading curves by optimal selection of tiles from printed color images

Bugnon

Hersch

2012

J. Electron. Imaging

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The Yule-Nielsen modified spectral Neugebauer model (YNSN) enables predicting reflectance spectra from ink surface coverages of halftones. In order to provide an improved prediction accuracy, this model is enhanced with an ink spreading model accounting for ink spreading in all superposition conditions (IS-YNSN). As any other spectral reflection prediction model, the IS-YNSN model is conceived to predict the reflection spectra of colorconstant patches. Instead of color-constant patches, we investigate if tiles located within color images can be accurately predicted and how they can be used to facilitate the calibration of the ink spreading model. In the present contribution, we detail an algorithm to automatically select image tiles as uniform as possible from color images by relying on their CMY or CMYK pixel values. The tile selection algorithm incorporates additional constraints relying on surface coverages of the inks. We demonstrate that an ink spreading model calibrated with as few as 5 to 10 optimally chosen image tiles allows the corresponding YNSN model to provide accurate spectral predictions. 1 1 This is an extended version of a paper previously published at the SPIE/IS&T

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Physical Evaluation of the Quality of Color Halftone

Yang¹

2015

Handbook of Digital Imaging

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This chapter presents the fundamental aspects for quantitative quality evaluations of color halftone. It begins with the basics of ink transfer and ink setting of printing technologies. Ink–paper interaction in the forms of ink spreading and ink penetration and their impacts on color reproduction are specially addressed. This is followed by brief description of color measurement, explaining the fundamental principles and devices. Then, a through illustration of how lateral light scattering inside a turbid substrate leading to the optical dot gain is given. Finally, details about how to determine physical dot gain and optical dot gain, by means of model‐aided approaches or imaging‐processing techniques, are presented.

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Deducing Ink Spreading Curves from Reflection Spectra Acquired Within Printed Color Images

Cited by 7 publications

References 13 publications

Recovering neugebauer colorant reflectances and Ink‐spreading curves from printed color images

Recovering neugebauer colorant reflectances and Ink‐spreading curves from printed color images

Calibrating ink spreading curves by optimal selection of tiles from printed color images

Physical Evaluation of the Quality of Color Halftone

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