Colour-appearance modeling using feedforward networks with Bayesian regularization method-part I: Forward model

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12 Citations (Scopus)

Abstract

In this article, a method of predicting colour appearance (from colorimetric attributes to colour-appearance attributes, i.e., forward model) using an artificial neural network is presented. The neural network model developed is a multilayer feedforward neural network model for predicting colour appearance (FNNCAM for short). The model was trained by LUTCHI colour-appearance datasets. The Levenberg-Marquardt algorithm is incorporated into the back-propagation procedure to accelerate the training of FNNCAM and the Bayesian regularization method is applied to the training of neural networks to improve generalization. The results of FNNCAM obtained are quite promising.
Original languageEnglish
Pages (from-to)424-434
Number of pages11
JournalColor Research and Application
Volume25
Issue number6
DOIs
Publication statusPublished - 1 Jan 2000

Keywords

  • Back-propagation
  • Bayesian regularization
  • Colour-appearance model
  • Feedforward neural networks
  • Levenberg-Marquardt algorithm

ASJC Scopus subject areas

  • Human Factors and Ergonomics
  • Chemistry(all)
  • Chemical Engineering(all)

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