Application of Near Infrared Spectroscopy in the Analysis of Printing Color Detection


Article Preview

For the fast and exact detection of printing color, we combine the near infrared (NIR) spectroscopy technique with partial least square (PLS) to build the detection model of printing color. Applying the 144 samples of spectral curve which obtained by the near infrared spectroscopy randomly separated into calibration set and validation set, and base on the 120 calibration set data to establish the prediction model of printing color by PLS, then this model is employed for predicting the color of the 24 validation set. The RMSEC of the 24 blocks’ color parameters L*, a*, b*, E are 0.73, 2.26, 3.03 and 1.09 respectively; The RMSEP are 0.97, 2.77, 3.57 and 1.34 respectively. Those results tell that the NIR spectrum and blocks’ color parameters L*, a*, b*, E could accurately establish a quantitative regression model, applying such model also can accurately predict unknown samples, and the results approximate to the original reference data. The use of near infrared spectroscopy to detect the printed matter nondestructively is feasible, and lays the foundation for the further analysis and establishment of printing chroma model.



Edited by:

Ouyang Yun, Xu Min, Yang Li and Liu Xunting




H. W. Lu et al., "Application of Near Infrared Spectroscopy in the Analysis of Printing Color Detection", Applied Mechanics and Materials, Vol. 262, pp. 59-64, 2013

Online since:

December 2012




[1] Verikas A, Lundstrom J, Bacauskiene M, et al. Expert Systems with Applications. Vol. 38 (2011), p.13441.

[2] Dąbrowa T, Gajadhur M. Surface Coatings International Part B: Coatings Transactions. Vol. 89 (2007), p.305.

[3] Andersson M. The International Society for Optical Engineering, CA, USA. Vol. 6493 (2007), p.134.

[4] Liu F, He Y. Food Chemistry. Vol. 115 (2009), p.1430.

[5] Iwamoto R. Applied Spectroscopy. Vol. 63 (2009), p.354.

[6] Beatriz GA, Olga MC, Jesus. Sensors and Actuators B. Vol. 129 (2008), p.977.

[7] Jackman P, Sun DW, Du CJ. Pattern Recognition. Vol. 42 (2009), p.751.

[8] Lee JH, Chong MG. Food Science and Biotechnology. Vol. 2 (2009), p.60.

[9] Alemea HG, Letícia M. Talanta. Vol. 78 (2009), p.1422.

[10] Bellon V, McBratney A. Soil Biology and Biochemistry. Vol. 43 (2011), p.1398.

[11] Heigl N, Petter CH, Lieb M, et al. Vibrational Pectroscopy. Vol. 7 (2009), p.155.

[12] Rao YL, Xiang BG, Zhou XH. Journal of Food engineering. Vol. 93 (2009), p.249.

[13] Richter MM, Zierhut KC, Dresler T. Journal of Neural Transmission. Vol. 3 (2009), p.267.

[14] Salvador MA, Almeida P, Reis LV. Dyes and Pigments. Vol. 82(2009), p.118.

[15] Guan LM, Hu GS, Lu HW, et al. Journal of Central South University. Vol. 40 (2009), p.1655.

[16] He C, Chen LJ, Yang ZL, et al. Bioresource Technology. Vol. 110 (2012), p.314.

[17] Chen JY, Iyo C, Teradab FJ. Journal of Near Infrared Spectroscopy. Vol. 10 (2002), p.301.

[18] Sohn JH, Atzeni M, Zeller L. Sensors and Actuators, B: Chemical. Vol. 131(2008), p.230.