Assessment of hyperspectral imaging system for colour measurement

Chlebda, Damian K.; Rogulska, Anna; Łojewski, Tomasz

doi:10.1016/j.saa.2017.05.037

Cited by 18 publications

(9 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…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%

mentioning

confidence: 99%

“…In this paper, the uniform CIE (1976) L*a*b* color space is used, where the distance of color space is proportional to the chromatic aberration of vision, overcoming the inconsistent color distinguishing ability between regions with different brightness and chrominance in a non-uniform color space. 8 For multi-colored printed fabrics, color segmentation is necessary after color measurement in an automatic color analysis system. Color segmentation is the process whereby a printed fabric is divided into a few regions that have uniform and similar color features so that the color values of each region can be calculated independently.…”

mentioning

confidence: 99%

See 2 more Smart Citations

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

Zhang

et al. 2019

Textile Research Journal

View full text Add to dashboard Cite

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.

show abstract

Section: Comparison Of the Proposed Algorithm And Other Segmentation mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

See 1 more Smart Citation

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

Zhang

et al. 2019

Textile Research Journal

View full text Add to dashboard Cite

show abstract

“…The results showed that the hyperspectral imaging system with high spatial resolution could be used for spectral and color measurement and industry analysis 17 . In a recent study, Chlebda et al evaluated the hyperspectral imaging system performance and proved that the hyperspectral imaging system could be considered an important alternative to conventional colorimeters in the field of art conservation 18 . In the textile field, Zhang et al proposed a novel single yarn segmentation method based on spectral matching through adaptively setting a threshold of Fréchet distance values to the color measurement of a single yarn using a hyperspectral imaging system, and the proposed method was proved to be better than the modified K‐means clustering method 19 …”

Section: Introductionmentioning

confidence: 99%

Evaluation of the color measurement based on a microscopic hyperspectral imaging system

Qiu

Chen

Zhou

et al. 2021

Color Research & Application

View full text Add to dashboard Cite

In order to make a color assessment for micron‐grade materials such as a single fiber, a non‐destructive and push‐broom microscopic hyperspectral imaging system (MHIS) was set up consisting of a stereomicroscope, an imaging spectrograph, and a digital detector. The performance of this system for acquiring accurate and repeatable information, such as spectral and colorimetric values, was investigated. The experimental results show that the system has an excellent spatial resolution, repeatability, and accuracy. The spatial resolution with a ×1.5 auxiliary objective lens was down to 90.244 lp mm−1 (5.54 μm). The average ΔE00 of the tested patches in the ColorChecker Mini chart was between 0.15 and 0.40, and the color measurement repeatability was acceptable. Color difference ΔE00 and the standard variation of spectral wavelength between ×2.5 and ×4.5 magnification were larger than those at lower magnifications. It can be concluded that the MHIS can identify colorimetric values of the materials and detect the color changes sensitively with a high spatial resolution at micron‐grade.

show abstract

“…Одним из основных препятствий к получению высокой повторяемости результатов восстановления спектральной плотности яркости по данным многоканальной съемки на практике является погрешность измерений сигнала приемника излучения [4,5]. Введение погрешности в моделирование метода многоканальной гиперспектрометрии позволит проверить надежность указанного метода и определить его место в современной науке и технике, в том числе привести математическое обоснование применения метода для получения гиперспектральных данных в практических приложениях [6,7].…”

Section: Introductionunclassified

Сравнительный Анализ Методов Решения Некорректных Обратных Задач Для Многоканальной Гиперспектрометрии

Гурылева¹,

Хорохоров²,

Латышев³

2019

Журнал Технической Физики

View full text Add to dashboard Cite

A comparative analysis of various implementations of multichannel recording using optical filters is performed to improve the spectral resolution of multichannel hyperspectrometers at maintaining the high spatial resolution. The computing power of different means of multichannel data processing is considered as well. The recovery of spectral brightness density using multichannel recording data is shown to be an incorrect task. The methods proposed to solve it are wavelet transformation, Tikhonov’s regularization approach, and Godunov method. The spectral brightness density is simulated using the multichannel recording results taking into account the measurement error. The applicability limits are established for each method. It is supposed that the Tikhonov method is more resistant to measurement errors. Various approaches for selecting optical filters that participate in the multichannel recording are compared with respect to the final accuracy of spectral brightness density reconstruction using the recording data, which evidences the benefits of the classical method. The optimal combination of the amount of optical filters and the number of recording channels is found as well. The wide application necessitates three channels with four optical filters and eight channels with two optical filters.

show abstract

Assessment of hyperspectral imaging system for colour measurement

Cited by 18 publications

References 26 publications

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

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

Evaluation of the color measurement based on a microscopic hyperspectral imaging system

Сравнительный Анализ Методов Решения Некорректных Обратных Задач Для Многоканальной Гиперспектрометрии

Contact Info

Product

Resources

About