摘要
A novel method for spectral characterization of scanner was proposed in this paper, which combined the principal component analysis （PCA） and back propagation （BP） artificial neural network （ANN）. The natural color system （NCS） color patches were adopted as the color targets. The accuracy of this method was evaluated by spectral root mean square （SRMS） error and the CIEDE2000 color difference specification. The experimental results showed that six principal components were appropriate and the spectral characterization accuracy was outstanding when a 3-20-6 BP net structure was used to estimate the scalars from the scanner red/green/blue （RGB） signals.
A novel method for spectral characterization of scanner was proposed in this paper, which combined the principal component analysis （PCA） and back propagation （BP） artificial neural network （ANN）. The natural color system （NCS） color patches were adopted as the color targets. The accuracy of this method was evaluated by spectral root mean square （SRMS） error and the CIEDE2000 color difference specification. The experimental results showed that six principal components were appropriate and the spectral characterization accuracy was outstanding when a 3-20-6 BP net structure was used to estimate the scalars from the scanner red/green/blue （RGB） signals.
