The Use of Fundamental Color Stimulus to Improve the Performance of Artificial Neural Network Color Match Prediction Systems

In the present investigation attempts were made for the first time to use thefundamental color stimulus as the input for a fixed optimized neural network match predictionsystem. four sets ofdata having different origins (i.e. different substrate, different colorant sets anddifferent dyeing procedures) were used to train and test the performance ofthe network. the resultsshowed that the use offundamental color stimulus greatly reduces the errors as depicted by themse and a cave data and improves the performance of the neural network prediction system.additionally the use of fundamental color stimulus makes provisions for predicting theconcentrations of one data set whilst being trained by a second data set of completely differentorigin.