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Volume: 27 | Article ID: art00029
Color Space Transformation using Neural Networks
  DOI :  10.2352/issn.2169-2629.2019.27.29  Published OnlineOctober 2019

We investigated how well a multilayer neural network could implement the mapping between two trichromatic color spaces, specifically from camera R,G,B to tristimulus X,Y,Z. For training the network, a set of 800,000 synthetic reflectance spectra was generated. For testing the network, a set of 8,714 real reflectance spectra was collated from instrumental measurements on textiles, paints and natural materials. Various network architectures were tested, with both linear and sigmoidal activations. Results show that over 85% of all test samples had color errors of less than 1.0 ΔE2000 units, much more accurate than could be achieved by regression.

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Lindsay MacDonald, "Color Space Transformation using Neural Networksin Proc. IS&T 27th Color and Imaging Conf.,  2019,  pp 153 - 158,

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Copyright © Society for Imaging Science and Technology 2019
Color and Imaging Conference
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