Color space conversion via gamut-based color samples of printer

Because many types of electronic imaging devices are now available, cross-m edia color reproduction technology has received widespread attention due to the need to provide accurate color stimuli for different devices. In the c ase of cross-media color reproduction between a monitor and a printer, RGB has to be converted into a de vice-independent color space in order to tran slate the color information between the two devices. Thereafter, gamut mapp ing is used to compensate for any gamut mismatch and device-independent col ors have to be re-converted into output colors such as CMY control values f or printing. For color conversion between device colors and device-independ ent colors, empirical representation using sample measurements is currently widely utilized. In the case of the printer, color samples are uniformly s elected in the colorant space, printed as color patches, and then measured. However, because these color samples are not evenly distributed inside the printer gamut, the color conversion error is increased. Accordingly, this article introduces a color-sampling algorithm for a printer to reduce the e rror in color conversion, and the performance is analyzed via color convers ion experiments using three conversion methods, regression, neural network, and interpolation.