A method of printer modeling with the spectral reflectance curves using error back propagation

Most color imaging devices exhibit color distortions due to nonlinear component characteristics. Among color correction techniques, the most popular is device characterization. Generally there are two parts in printer characterization using a neural network, i.e. printer modeling and printer controller. This paper presents a method of printer modeling with spectral reflectance values using error back propagation. In experiments, we used an ink jet printer. First we print many color patches using known CMY values, and measured these patches with spectral reflectance values at wavelengths. The data set of the measured values and the input values were split into the validation set for assessing the performance of the trained network and the training sets. For training we took CMY values for the input nodes and reflectance values for the target values of the output nodes. The input layer of the network receives input as a CMY vector. The output represents spectral reflectance at certain wavelengths. To get a better performance, we change the network scheme. For the evaluation, we transformed spectral reflectance values to XYZ values. With this model, we can make a printer controller, the reverse of a printer model. Printer controller takes XYZ values for input and CMY for output. If the printer prints with controller CMY, we have the same L*a*b* between printed color patches and input value of the printer controller. From a global point of view, this total system represents a mapping from a target L*a*b* value to the output L*a*b* value of the printer