Characterization of Color Devices by Polynomial Regression


As color devices may lose accuracy during a period of time, characterization should be made to calibrate them. A 4th order polynomials regression method is proposed for color characterization. In the experiment, different forms of polynomials are used to represent the relationship of RGB and L*a*b*, and the result shows the new proposed 4th order polynomials have smaller errors than other forms of polynomials. What's more, the 3D LUT and neural network method are also compared with our method, and the result suggested that all these three method have the error about 2 color difference units, which is far lower than the replicate threshold of 6. While our method takes up the least time in experiment, which is significant and may broaden its application in image processing.

  • Abstract
  • Key Words
  • 1. Introduction
  • 2. Ploynomial Regression Used in Color Characteriztion
  • 3. Experiment and Analysis
  • 4. Summaries
  • References
Topics: Polynomials

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In