Color printer characterization using optimization theory and neural networks
US6480299B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 25, 1998 |
| Grant date | Nov 12, 2002 |
| Priority date | — |
| Expiry date | Nov 25, 2018 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04N1/6058
- WIPO fieldAudio-visual technology
- WIPO sectorElectrical engineering
Abstract
A color management method/apparatus generates image color matching and International Color Consortium (ICC) color printer profiles using a reduced number of color patch measurements. Color printer characterization, and the generation of ICC profiles usually require a large number of measured data points or color patches and complex interpolation techniques. This invention provides an optimization method/apparatus for performing LAB to CMYK color space conversion, gamut mapping, and gray component replacement. A gamut trained network architecture performs LAB to CMYK color space conversion to generate a color profile lookup table for a color printer, or alternatively, to directly control the color printer in accordance with the a plurality of color patches that accurately. represent the gamut of the color printer. More specifically, a feed forward neural network is trained using an ANSI/IT-8 basic data set consisting of 182 data points or color patches, or using a lesser number of data points such as 150 or 101 data points when redundant data points within linear regions of the 182 data point set are removed. A 5-to-7 neuron neural network architecture is preferred to perform the LA…
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.