Colour matching comparison between spectrophotometric and multispectral imaging measurements

Luo, Lin; Shen, Hui Liang; Shao, Si Jie; Xin, John Haozhong

doi:10.1111/cote.12191

Cited by 5 publications

(5 citation statements)

References 11 publications

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“…Our algorithm and the other segmentation algorithms were also compared for time complexity (Figure 11). This involves determining the sum of time searching for the optimal number of clusters (2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15) and the time required to calculate the SI values. These results show the time taken on the algorithms while tested on the above five printed fabrics, showing that our algorithm performs more efficiently than other segmentation algorithms.…”

Section: Comparison Of the Proposed Algorithm And Other Segmentation mentioning

confidence: 99%

“…A multispectral imaging system was proposed, which can obtain multi-band spectral reflectance, improving color measurement accuracy greatly. 5,6 However, its accuracy depends on the number of bands and the selected bands of interest. In addition, the more complex operation of this system means it only can be used in the laboratory for offline- and batch color measurement.…”

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confidence: 99%

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Multi-color measurement of printed fabric using the hyperspectral imaging system

Zhang

et al. 2019

Textile Research Journal

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Printed fabrics usually have multiple colors and intricate patterns, which make it difficult to directly measure the colors of the printed fabrics with a traditional spectrophotometer. However, a hyperspectral imaging system (HIS) can measure multiple colors since it acquires the spectral reflectance of a continuous band at every point of the fabric. For multiple-color printed fabrics, color segmentation is also very important. In this paper, color measurement of printed fabrics using the HIS was implemented; an algorithm which combines the self-organizing map (SOM) algorithm and the density peaks clustering (DPC) algorithm was then proposed to automatically determine the number of colors on the printed fabric and accurately segment the color regions for measurement. Firstly, the SOM algorithm was used to identify the main clusters, the DPC algorithm with Silhouette Index was then used to identify the optimal number of colors and merge the clusters. Experimental results show that this algorithm not only automatically determines the optimal number of colors for printed fabric and achieves accurate color segmentation, but requires less time for execution.

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Section: Comparison Of the Proposed Algorithm And Other Segmentation mentioning

confidence: 99%

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confidence: 99%

Multi-color measurement of printed fabric using the hyperspectral imaging system

Zhang

et al. 2019

Textile Research Journal

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“…Through various image processing and machine learning techniques, MSI can measure colour in minute regions, such as yarns. 1,[8][9][10][11] Whiteness measurement has remained a critical endeavour across dentistry, 12,13 textiles, 14,15 paper, [16][17][18] and detergents. 19 For instance, inconsistent whiteness in large fabric batches risks rejection and financial losses.…”

Section: Introductionmentioning

confidence: 99%

“…MSI holds enormous potential for colour metrology, as it provides both spectral and spatial information. Through various image processing and machine learning techniques, MSI can measure colour in minute regions, such as yarns 1,8–11 …”

Section: Introductionmentioning

confidence: 99%

Fluorescent whiteness measurement of textiles by multispectral imaging system

Yao,

Wu,

et al. 2023

Coloration Technology

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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.

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“…This method has the disadvantage of high labor intensity and poor color measurement stability. 4,5 With the development of spectrophotometry, the spectral imaging and the digital imaging technologies, the fabric color measurement can be realized by electronic equipment, [6][7][8][9] providing an image basis for color segmentation of printed fabric based on machine vision.…”

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confidence: 99%

Color segmentation of multicolor porous printed fabrics by conjugating SOM and EDSC clustering algorithms

Qian

Wang

Huang

et al. 2022

Textile Research Journal

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In order to achieve accurate color segmentation of printed fabrics, the color segmentation algorithm combining the self-organizing maps neural network and the efficient dense subspace clustering was proposed in this paper. After pre-processing of the fabric image, the primary clustering was implemented by the self-organizing maps algorithm, then the secondary clustering was done by the efficient dense subspace clustering algorithm. The optimal silhouette coefficient is introduced into the clustering process of the efficient dense subspace clustering algorithm to determine the number of clustering centers automatically. Finally, by the post-processing including gray-scale transformation, binarization and open operation, the mis-segmentation of edge color was eliminated, making the algorithm more suitable for industrial application. Experiments were carried out and results show that the algorithm proposed in this paper can recognize the color of small areas accurately and segment the color of complex printed fabric images. The color segmented results of 20 printed fabrics show that the accuracy of the algorithm proposed in this paper reaches 88.3%.

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Colour matching comparison between spectrophotometric and multispectral imaging measurements

Cited by 5 publications

References 11 publications

Multi-color measurement of printed fabric using the hyperspectral imaging system

Multi-color measurement of printed fabric using the hyperspectral imaging system

Fluorescent whiteness measurement of textiles by multispectral imaging system

Color segmentation of multicolor porous printed fabrics by conjugating SOM and EDSC clustering algorithms

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