Color measurement of single yarn based on hyperspectral imaging system

Textile Research Journal

et al. 2020

Self Cite

For multi-color yarn-dyed fabrics which are cross-woven by yarns with different colors, the different colors cannot be directly measured by a traditional spectrophotometer because it can only obtain the average color of solid-color sample in the limited aperture. In this paper, a novel method for color segmentation and extraction for multi-color yarn-woven fabrics based on a Hyperspectral Imaging System (HIS) was proposed. First, the multi-color yarn-woven fabric images were acquired with the HIS. Then a space transformation based on Fréchet distance was used to transform the pre-processed hyperspectral fabric images into gray images, and then an improved watershed algorithm was used to segment the transformed gray images into different color regions. Finally, to solve the problems of over-segmentation with the improved watershed algorithm, an improved k-means clustering algorithm was adopted to merge the over-segmented color regions. The experimental results on four multi-color yarn-woven fabrics showed that the color segmentation accuracy of the proposed method outperformed the ordinary k-means, Fuzzy C-means (FCM), and Density peak cluster (DPC) algorithms on evaluation indexes of compactness (CP) and separation (SP), and the execution efficiency was improved by at least 55%. Furthermore, the color difference between the proposed method and the spectrophotometric measurements ranged from 0.60 to 0.88 CMC (2:1) (Color Measurement Committee) units, which almost satisfied the accuracy of color measurement.

Section: Hyperspectral Image Acquisition Based On the Hismentioning

confidence: 99%

Color segmentation and extraction of yarn-dyed fabric based on a hyperspectral imaging system

Textile Research Journal

et al. 2020

Self Cite

“…In recent years, multispectral imaging (MSI) and hyperspectral imaging (HSI) systems have garnered substantial research interest [1][2][3][4][5][6][7] for enabling accurate colour reproduction and measurement. MSI holds enormous potential for colour metrology, as it provides both spectral and spatial information.…”

Section: Introductionmentioning

confidence: 99%

Fluorescent whiteness measurement of textiles by multispectral imaging system

Yao,

Wu,

et al. 2023

Coloration Technology

Accurate whiteness measurement is critical across various industries including textiles, paper, and detergents. With the advent of fluorescent whitening agents (FWAs), the assessment of whiteness has evolved from simply measuring reflectance to determining the spectral radiance factor (SRF) of materials. While multispectral imaging (MSI) can effectively measure object reflectance and colour, its accuracy is compromised by FWAs that significantly augment spectral reflectance. Thus, reliable whiteness measurement requires the determination of both reflectance and SRF. This article presents the design of a specialised light source equipped with an ultraviolet (UV) filter to provide adjustable illumination within an integrating sphere system. By tuning the position of the UV filter, multispectral images are captured of a fabric under varying UV exposures. These images are subsequently processed and combined to reconstruct full‐range visible spectrum information. This approach is shown to achieve high accuracy and spatial uniformity in quantifying the whiteness of textiles using MSI.

“…Xiao et al 11 used the HIS to collect the spectral reflectance of the fabric, and established the neural network model to predict the dyeing recipe of the fabric. Zhang et al 12 used the HIS to measure a single yarn and establish a model to solve the problem of radiation intensity difference at different positions of the yarn. Zhang et al 13 also used the abundant spectral reflectance information measured by HIS to achieve the color segmentation for printed multicolor fabrics.…”

Section: Introductionmentioning

confidence: 99%

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

Liu

Color Research & Application

et al. 2021

Self Cite

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.