Colorimetric modeling for vision systems

Gao Wei Chang, Yung Chang Chen

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

A colorimetric modeling technique is proposed to give a computational model associated with colorimetry so that the representation of color acquired from camera imaging is accurate and meaningful. First of all, the camera spectral responses are estimated and the colorimetric quality is evaluated to reveal the feasibility of this work. In the modeling process, we present a spectral matching method and an approach of determining a reference-white luminance. As a result, the acquired color and the true (or measured) color can be well coordinated, with the strength of a global illumination or display white, in a perceptually uniform color space, e.g., in CIE 1976 L*a*b* space (abbreviated as CIELAB). Then, lower-degree polynomial regression is employed to eliminate color errors due to the mismatch between spectral response functions. Experimental results indicate that the root-mean-square Δ E*ab value (i.e., color error) from the degree-3 polynomial regression is less than a just-noticeable difference (about 2,3) in CIELAB. It appears that the proposed technique can establish an accurate colorimetric model for vision systems.

Original languageEnglish
Pages (from-to)432-444
Number of pages13
JournalJournal of Electronic Imaging
Volume9
Issue number4
DOIs
Publication statusPublished - 2000 Oct

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Computer Science Applications
  • Electrical and Electronic Engineering

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