1. Reducing the number of measuring points of the LED-based colorimetric probe.
- Author
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Arbanas, Milos, Batinic, Branislav, Bajic, Jovan, Vasiljevic-Toskic, Marko, Brkic, Miodrag, and Rajs, Vladimir
- Subjects
COLORIMETRY ,ARTIFICIAL neural networks ,ELECTROMAGNETIC spectrum ,MACHINE learning ,LED displays - Abstract
In this paper, reducing the number of necessary measuring points for estimating a reflected electromagnetic spectrum of a printed color patch is presented. In our previous work, a machine learning-based method was proven to be superior to Cubic Hermite interpolation in estimating spectrum based on six measured values provided by measuring reflection of six LED sources (400 nm, 457 nm, 517 nm, 572 nm, 632 nm, and 700 nm). Now, the new hypothesis is that the number of measuring points LEDs could be decreased without the significant loss of the spectrum estimation. The ECI2002 test chart was used to create the dataset, which was further divided into training and test subset. For all the colors on the test chart, the measurements were performed on printed patches with the device proposed in our previous work, as well as with the commercial spectrophotometer X-Rite i1 Publish Pro2, which were then used as the ground truth, or reference values. The Artificial Neural Networks were trained to estimate spectrums based on measurements acquired with our device. The results proved satisfactory even when the number of measuring points is reduced from six to three RGB LEDs (457 nm, 517 nm, and 632 nm). [ABSTRACT FROM AUTHOR]
- Published
- 2022
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