Replicated multi-channel sensors for decucing ink thicknesses in color printing devices

Abstract

A method and computing system are proposed for deducing ink thickness variations from solid-state multi-sensor measurements performed online on a printing press or printer. The computed ink thickness variations enable controlling the ink deposition and therefore the color accuracy. Ink thickness variations are expressed as ink thickness variation factors incorporated into an ink thickness variation and sensor response enhanced spectral prediction model. The ink thickness variation computing system comprises multi-channel sensor devices (e.g. red, green, blue, near infra-red), a processing module, and a computing system. The multi-channel sensor devices are replicated over the width of the print sheet. Preferably embodied by Single Photon Avalanche Diodes (SPADs), due to their high-speed acquisition capabilities, they provide responses according to the reflectance of small area segments within a print sheet. The processing module accumulates the digital sensor responses and forwards them to the computing system, which deduces the ink thickness variations.

Description

[0001] The present patent application is a continuation-in-part of U.S. patent application Ser. No. 10 / 631743, Prediction model for color separation, calibration and control of printers, inventors R. D. Hersch, P. Emmel, F. Collaud, filed Aug. 1, 2003.BACKGROUND OF THE INVENTION [0002] The present invention relates to the field of color printing and more specifically to the control of color printer actuation parameters. It discloses a new concept of non-expensive replicated illuminating and sensor devices placed on the printer in face of the moving paper sheets as well as a spectral prediction model extension adapted to the proposed set of illuminating and sensor devices. [0003] Color control in printing presses is desirable in order to ensure that effectively printed colors correspond to the desired colors, i.e. the colors expected by the prepress color separation stage. Color consistency is desirable both across consecutive sheets of a multi-sheet print job and also from print job...

AI Technical Summary

Benefits of technology

[0018] The present invention proposes a method and a computing system for deducing ink thickness variations from multi-channel sensor responses acquired online during print operation of a printing press or a printer. Acquiring the ink thickness variations online and in real-time enables regulating the ink deposition process during normal print operation. Real-time online control of the ink deposition process enables keeping a high color accuracy from print sheet to print sheet and from print job to print job. This is especially important if the ink deposition process is not stable when working in open loop mode.

[0019] Ink thickness variations are expressed as ink thickness variation factors incorporated into an ink thickness variation and sensor response enhanced spectral prediction model. The method for computing ink thickness variations comprises both calibration and ink thickness variation computation steps. The calibration steps comprise the measurement and adjustment of paper reflectance, possibly the calculation of internal paper reflectance, the calculation of ink transmittances from measured reflectances, the computation of scalar ink thicknesses of solid superposed inks and, in order to account for ink spreading, the computation of effective surface coverages of single ink halftones in different superposition conditions. By interpolation, we obtain the effective surface coverage curves mapping nominal to effective surface coverages of single ink halftones in different superposition conditions. The calibration steps can be divided into offline and online calibration steps. The offline calibration steps require specially printed patches such as solid ink and solid ink superposition patches on which spectral reflectance measurements are performed. From these spectral reflectance measurements, the internal reflectance of paper and the transmittance of the inks are obtained. The optional online calibration steps improve the calibration in case of changes in the printer operating conditions, e.g. a change in temperature, a change of paper, or a new set of inks which differs from the previous set. Online calibration steps are performed only with multi-channel sensor responses from printed area segments located within the printed sheet. They may comprise the recalibration of the paper reflectance, and possibly the calibration or recalibration of the effective surface coverage curves. They may also comprise deducing reference thickness variations which are then used to compute thickness variations normalized in respect to these reference thickness variations.

[0020] In respect to the ink thickness variation computation steps, the thickness variation and sensor response enhanced spectral prediction model comprises as solid colorant transmittance of two or more superposed solid inks the transmittance of each of the contributing superposed ink raised to the power of a product of two variables, one variable being the superposition condition dependent ink thickness and the other variable being the ink thickness variation factor. The ink thickness variations are fitted by minimizing a distance metric between predicted multi-channel sensor responses and acquired multi-channel sensor responses, the predicted multi-channel sensor responses being computed according to the ink thickness variation and sensor response enhanced spectral prediction model.

[0023] If the nominal surface coverages of the halftone area segment on which thickness variations are to be performed are unknown, it is possible, in addition to the calibration of the transmittances and the thicknesses of the inks, to measure sensor responses from a reference print under reference settings and to deduce with the thickness enhanced spectral prediction model the corresponding reference effective surface coverages. The sensor responses are then predicted with the deduced reference effective surface coverages. Ink thickness variations are computed by minimizing a distance metric between predicted sensor responses and measured sensor responses. The computed ink thickness variations represent ink thickness variations in respect to the reference print.

Problems solved by technology

Due to the large number of parameters which need to be taken into account, this solution seems complex and costly.

Such high order polynomials are known to oscillate between the known values of input / output variables and therefore do not always provide a correct mapping between sensor input variables and ink dot size output variables.

Since these two conversion tables are deduced from experiments which may have been performed under different printing conditions (temperature, settings of the press, etc.), the control of the ink aperture is not precisely adapted to the current operating conditions of the press.

In addition, experience shows that it is very difficult to control the ink feed of 4 inks (c,m,y,k) with a 3-sensor system only.

That method does not consider controlling the ink feed rate according to sensor responses of illuminated polychromatic halftones.

It is known that the Kubelka-Munk model only works on uniformly diffuse layers and is therefore not applicable to halftones.

But due to the uncertainty between joint variations in the ink thicknesses of cyan, magenta, and yellow and a variation in thickness of black, the method does not work well for the set of cyan, magenta, yellow and black inks.

In addition, that method does not teach how to calibrate the prediction model with halftones that are an integral part of a printed document page delivered to a customer.

This patent application does neither teach how to obtain ink thickness control parameters from polychromatic halftone patches nor from halftones being part of the actual printed document pages.

Images