Research on Spectral Measurement Method for Content of Bicolor Mixed Ink
Abstract
To achieve consistent color reproduction of printed products and accurate measurement the content of mixed ink has always been an important research topic in the printing industry. This paper proposes a spectral-based method for measuring the content of dual-color mixed printing ink, aiming to solve the difficulty in determining the specific content of the base color in the same ratio of dual-color ink by using spectral analysis. First, a composite filtering method combining median filtering and wavelet transform was compared and selected for spectral preprocessing. Then, three methods, namely the successive projections algorithm (SPA), competitive adaptive reweighted sampling method (CARS), and stable competitive adaptive weighted sampling method (SCARS), were used to extract feature wavelengths from the preprocessed information. Based on partial least squares regression (PLSR), four models, PLSR, SPA-PLSR, CARS-PLSR, and SCARS, were established for predictive analysis. To further test the model, the SCARS-PLSR model was used for predictive analysis of magenta-cyan, yellow-magenta, and yellow-cyan binary samples with a mass fraction ratio of 0.5. The results showed that the SCARS-PLSR model has the best predictive performance, with RMSE and R2 values of 0.0052, 0.0002, 0.0004 and 0.9989, 0.9999, 0.9999, respectively. This indicates that this study can accurately determine the content of dual-color ink by spectral analysis.
About the Authors
S. FangChina
Beijing
W. Zhang
China
Beijing
R. Zhang
China
Beijing
F. Jiang
China
Beijing
Q. Liu
China
Beijing
References
1. F. F. Liu, Y. L. Shen, S. W. Zhan, Y. Wang, Y. Mou, S. L. Dong, J. W. He, J. Appl. Spectrosc., 90, No. 1, 108–115 (2023).
2. M. A. Ivanova, E. K. Nefedova, E. M. Mal'tseva, A. V. Kalensii, A. A. Zvekov, J. Appl. Spectrosc., 89, No. 5, 905–912 (2022).
3. H. Aboughaleb Ibrahim, M. Matboli, M. Shawky Sherif, Aref Mohamed Hisham, H. El-Sharkawy Yasser, QJM: An Int. J. Medicine, 114, Issue Supplement1 (2021).
4. M. Ristova, M. Skenderovska, T. Jovkovski, J. Appl. Spectrosc., 89, No. 5, 967–973 (2022).
5. L. L. Trotsiuk, E. S. Ton, V. I. Tsvirka, L. N. Survilo, S. I. Lishik, O. S. Kulakovich, A. A. Ramanenka, V. V. Krukov, Y. V. Trofimov, S. V. Gaponenko, J. Appl. Spectrosc., 89, No. 5, 869–873 (2022).
6. Z. Meng, S. Li, L. Haisu, X. Ziyan, S. Biquan, J. Appl. Spectrosc., 89, No. 1, 180–183 (2020).
7. M. Mayu, U. ShuHei, T. Hayato, K. Shintaro, Y. Hiroharu, Anal. Sci.: Int. J. Japan Soc. for Anal. Chem. (2023).
8. R. Yang, J. Kan, J. Appl. Spectrosc., 87, No. 10, 184–193 (2020).
9. R. L. Heckaman, J. Ho, SID Symposium Digest of Technical Papers, 47, No. 1, 723–726 (2016).
10. Z. He, R. Zhang, B. Ning, J. Zhao, G. Cheng, Optik, 216, 164946 (2020).
11. G. Diogo, Y. Burak, C. Pinar, J. W. Michael, Dental Materials: Official Publication of the Academy of Dental Materials, 38, No. 9, 1452–1458 (2022).
12. Y. Ohno, Society of Imaging Science and Technology, 16, 540–545 (2000).
13. Gabriela Krepper, et al., Spectrochim. Acta A: Mol. and Biomol. Spectrosc., 189, 300–306 (2018).
14. D. Daining, Y. Huichun, Y. Yong, Y. Yunxia, L. Zhaozhou, L. Fang, Analyt. Lett., 56, No. 8, 1216–1228 (2023).
15. W. Cai, Y. Li, X. Shao, Chemometrics and Intell. Lab. Syst., 90, No. 2, 188–194 (2007).
16. Q. Han, H. Wu, C. Cai, L. Xu, R. Yu, Analyt. Chim. Acta, 612, No. 2, 121–125 (2008).
17. K. Zheng, Q. Li, J. Wang, J. Geng, P. Cao, T. Sui, X. Wang, Y. Du, Chemometrics and Intell. Lab. Syst., 112, 48–54 (2012).
18. X. Zhang, W. Li, B. Yin, W. Chen, D. P. Kelly, X. Wang, K. Zheng, Y. Du, Spectrochim. Acta A: Mol. and Biomol. Spectrosc., 114, 350–356 (2013).
19. Y. Chuanqi, H. Weidong, X. Jing, Y. Huaguang, Z. Yuan, Road Materials and Pavement Design, 23, No. 4, 958–972(2022).
Review
For citations:
Fang S., Zhang W., Zhang R., Jiang F., Liu Q. Research on Spectral Measurement Method for Content of Bicolor Mixed Ink. Zhurnal Prikladnoii Spektroskopii. 2024;91(3):464.