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Evaluation and consistency calibration of hyperspectral imaging system based on liquid crystal tunable filter for fabric color measurement.

Authors :
Zhang, Jianxin
Liu, Yue
Zhang, Xinen
Hu, Xudong
Source :
Color Research & Application. Apr2022, Vol. 47 Issue 2, p401-415. 15p.
Publication Year :
2022

Abstract

The Hyperspectral Imaging System can obtain the spectral response value of each pixel in a fabric sample image while being applied to fabric color measurement. Compared with the common grating Hyperspectral Imaging System, the Hyperspectral Imaging System based on Liquid Crystal Tunable Filter (LCTF) has the advantages of small size, high spatial resolution, and easy integration, which has potential application prospects in textile industry. In this article, the performance of the LCTF Hyperspectral Imaging System for fabric color measurement was evaluated, and an improved model for calibrating the consistency between it and Datacolor 650 was proposed. First, the 210 Pantone cotton color cards were used as samples to study the color repeatability and reproducibility of the LCTF Hyperspectral Imaging System. For evaluation its color measurement ability, the measured reflectance values were converted to the CIELAB color space and compared with those of Datacolor 650. Then, a Radial Basis Function neural network model was proposed to calibrate the color consistency between LCTF Hyperspectral Imaging System and Datacolor 650 which can fully use the reflectance information of the whole band instead of only adjacent wavelengths. Experimental results show that the LCTF Hyperspectral Imaging System can accurately measure the fabric color with good repeatability and reproducibility, and the consistency between the two instruments was significantly improved based on the Radial Basis Function neural network model compared with the R model. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03612317
Volume :
47
Issue :
2
Database :
Academic Search Index
Journal :
Color Research & Application
Publication Type :
Academic Journal
Accession number :
155183949
Full Text :
https://doi.org/10.1002/col.22738