Journal of Textile Research ›› 2019, Vol. 40 ›› Issue (04): 140-144.doi: 10.13475/j.fzxb.20180305205

• Machinery & Accessories • Previous Articles     Next Articles

Spectral reflectance piecewise partition model for characterizing digital inkjet printer

TIAN Quanhui1(), GU Ping1, ZHU Ming2   

  1. 1. Green Platemaking and Standardization Key Laboratory for Flexographic Printing, Shanghai Publishing and Printing College, Shanghai 200093, China
    2. School of Materials and Chemical Engineering, Henan University of Engineering, Zhengzhou, Henan 450007, China
  • Received:2018-03-22 Revised:2018-12-05 Online:2019-04-15 Published:2019-04-16

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Abstract:

In order to improve the quality of color reproduction of digital inkjet printing, this paper studied the spectral characteristics of the printer which is the key technology for the textile inkjet printing, and presented a spectral reflectance piecewise partition model (SRPPM) for characterizing digital textile inkjet printing. Based on the nonlinear relationship between the 31 dimensional spectral reflectance and the digital driving data of the ink-jet printer, the model partitioned according to the reflectance band, used the nonlinear high order polynomial to fit the characteristic conversion coefficient between the output driving data and the color spectral reflectance in different bands, and applied the spectral characteristics of the digital inkjet printer by the obtained conversion matrix. Experimental results with skill textile show that the 90% spectral errors of testing color samples are less than 0.001 2, the maximum spectral error is 0.001 9, and the average spectral error is 0.000 8. While the 90% color differences of testing color samples are less than 1.0 NBS, the maximum value is 5.709 9 NBS and the average value is 0.570 0 NBS.

Key words: digital inkjet printer, spectral characterization, spectral piecewise partition, device characterization

CLC Number: 

  • TS101.3

Fig.1

Relationship between input digital scalars and spectral reflectance at given wavelength of inkjet textile."

Fig.2

Framework of SRPPM"

Fig.3

Prediction and measurement of cyan (a), manga(b), yellow(c) and black(d) spectral reflectance"

Fig.4

Cumulative relative frequency distribution of spectral root mean square error"

Fig.5

Cumulative relative frequency distribution of color difference(ΔE2000)"

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