Although color has appeal for developers and consumers alike, color reproduction poses a major problem in many computer based applications including multimedia and desktop publishing. The problem arises because of the device-independence of color, and the way each device processes color. Matching the appearance of monitor and print images, and achieving satisfactory results is complex. Not only are there fundamental differences between computer screen (additive) and printers (subtractive), but subtractive color is in general more prone to errors due to dye inadequacies. In order 110 Expert Systems, May 1998, Vol. 15, No. 2 to control the error in porting color, different techniques have been applied. In this paper, the utilization of artificial neural networks as well as abductive modeling approaches to color error reduction are introduced from an RGB (Red Green Blue) color model perspective. Analysis of the results and on-going research issues are discussed.

Although color has appeal for developers and consumers alike, color reproduction poses a major problem in many computer based applications including multimedia and desktop publishing. The problem arises because of the device-independence of color, and the way each device processes color. Matching the appearance of monitor and print images, and achieving satisfactory results is complex. Not only are there fundamental differences between computer screen (additive) and printers (subtractive), but subtractive color is in general more prone to errors due to dye inadequacies. In order 110 Expert Systems, May 1998, Vol. 15, No. 2 to control the error in porting color, different techniques have been applied. In this paper, the utilization of artificial neural networks as well as abductive modeling approaches to color error reduction are introduced from an RGB (Red Green Blue) color model perspective.Analysis of the results and on-going research issues are discussed.