Paper
24 January 2012 Characterization of color scanners based on SVR
Author Affiliations +
Proceedings Volume 8292, Color Imaging XVII: Displaying, Processing, Hardcopy, and Applications; 829216 (2012) https://doi.org/10.1117/12.905230
Event: IS&T/SPIE Electronic Imaging, 2012, Burlingame, California, United States
Abstract
By researching the principle of colorimetric characterization method and Support Vector Regression (SVR), we analyze the feasibility of nonlinear transformation from scanner RGB color space to CIELAB color space based on SVR and built a new characterization model. Then we use the MATLABR2009a software to make a data simulation experiment to verify the accuracy of this model and figure out the color differences by CIEDE2000 color difference formula. Based on CIEDE2000 color difference formula, the average, the maximum and the minimum color differences of the training set are 1.2376, 2.5593 and 0.2182, the average, the maximum and the minimum color differences of the text set are 1.9318, 4.1421 and 0.4228. From the experimental results, we can make a conclusion that SVR can realize the nonlinear transformation from scanner RGB color space to CIELAB color space and the model satisfies the accuracy of scanner characterization. Therefore, SVR can be used into the color scanner characterization management.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Bin Li and Yi-xin Zhang "Characterization of color scanners based on SVR", Proc. SPIE 8292, Color Imaging XVII: Displaying, Processing, Hardcopy, and Applications, 829216 (24 January 2012); https://doi.org/10.1117/12.905230
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KEYWORDS
RGB color model

Scanners

Color difference

Data modeling

Error analysis

Eye models

Neural networks

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