Neural networks based colour measuring for process monitoring and control in multicoloured newspaper printing

This paper presents a neural networks based method and a system for colour measurements on printed halftone multicoloured pictures and halftone multic oloured bars in newspapers. The measured values, called a colour vector, ar e used by the operator controlling the printing process to make appropriate ink feed adjustments to compensate for colour deviations of the picture be ing measured from the desired print. By the colour vector concept, we mean the CMY or CMYK (cyan, magenta, yellow and black) vector, which lives in th e three- or four-dimensional space of printing inks. Two factors contribute to values of the vector components, namely the percentage of the area cove red by cyan, magenta, yellow and black inks (tonal values) and ink densitie s. Values of the colour vector components increase if tonal values or ink d ensities rise, and vice versa. If some reference values of the colour vecto r components are set from a desired print, then after an appropriate calibr ation, the colour vector measured on an actual halftone multicoloured area directly shows how much the operator needs to raise or lower the cyan, mage nta, yellow and black ink densities to compensate for colour deviation from the desired print. The 18 months experience of the use of the system in th e printing shop witnesses its usefulness through the improved quality of mu lticoloured pictures, the reduced consumption of inks and, therefore, less severe problems of smearing and printing through.