Research on Spectral Measurement Method for Content of Bicolor Mixed Ink

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 yellowcyan 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.