High quality color correction method combining neural networks with genetic algorithms

A variety of color correction technologies have been applied to hardcopies to eliminate the crosstalk caused by unwanted absorption in colorants. However, since the accuracy of color correction is not sufficient, an improvement in color correction technology is required as an aspect of the appearance of color devices. This paper proposes a new color correction method combining neural networks with genetic algorithms. An evaluation experiment of RMS color difference has been done with the chart pattern of 1331 colors inside the printer color gamut. As a result, it has been shown that the proposed method is qualitatively and quantitatively superior to the conventional color correction masking method using the least squares method