Color measurement of single yarn based on hyperspectral imaging system

2020 ◽  
Vol 45 (3) ◽  
pp. 485-494
Author(s):  
Jianxin Zhang ◽  
Junkai Wu ◽  
Xinen Zhang ◽  
Xudong Hu
Keyword(s):  
Hyperspectral Imaging ◽  
Imaging System ◽  
Color Measurement ◽  
Single Yarn

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

2020 ◽  
pp. 004051752095740
Author(s):  
Zhang Jianxin ◽  
Zhang Kangping ◽  
Wu Junkai ◽  
Hu Xudong
Keyword(s):  
Hyperspectral Imaging ◽  
Clustering Algorithm ◽  
Imaging System ◽  
Color Difference ◽  
Woven Fabrics ◽  
Woven Fabric ◽  
Color Segmentation ◽  
Color Measurement ◽  
Watershed Algorithm ◽  
Density Peak

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.

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

2019 ◽  
Vol 90 (9-10) ◽  
pp. 1024-1037
Author(s):  
Jianxin Zhang ◽  
Junkai Wu ◽  
Xudong Hu ◽  
Xinen Zhang
Keyword(s):  
Hyperspectral Imaging ◽  
Imaging System ◽  
Optimal Number ◽  
Color Segmentation ◽  
Color Measurement ◽  
Self Organizing Map ◽  
Density Peaks ◽  
Silhouette Index ◽  
Som Algorithm ◽  
Density Peaks Clustering

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.

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

2021 ◽  
Author(s):  
Kebin Qiu ◽  
Weiguo Chen ◽  
Hua Zhou ◽  
Chenglong Wang ◽  
Zhihua Cui
Keyword(s):  
Hyperspectral Imaging ◽  
Imaging System ◽  
Color Measurement

Mapping of fatty acids composition in shelled almonds analysed in bulk using a Hyperspectral Imaging system

LWT ◽  
2021 ◽  
Vol 138 ◽  
pp. 110678
Author(s):  
Irina Torres ◽  
Dolores Pérez-Marín ◽  
Miguel Vega-Castellote ◽  
María-Teresa Sánchez
Keyword(s):  
Fatty Acids ◽  
Hyperspectral Imaging ◽  
Imaging System ◽  
Fatty Acids Composition

Determination of Basic Density and Moisture Content of Loblolly Pine Wood Disks Using a near Infrared Hyperspectral Imaging System

2011 ◽  
Vol 19 (5) ◽  
pp. 401-409 ◽  
Author(s):  
Christian R. Mora ◽  
Laurence R. Schimleck ◽  
Seung-Chul Yoon ◽  
Chi N. Thai
Keyword(s):  
Moisture Content ◽  
Hyperspectral Imaging ◽  
Loblolly Pine ◽  
Near Infrared ◽  
Imaging System ◽  
Basic Density ◽  
Pine Wood

scholarly journals Nondestructive and rapid determination of lignocellulose components of biofuel pellet using online hyperspectral imaging system

2018 ◽  
Vol 11 (1) ◽  
Author(s):  
Xuping Feng ◽  
Chenliang Yu ◽  
Xiaodan Liu ◽  
Yunfeng Chen ◽  
Hong Zhen ◽  
...  
Keyword(s):  
Hyperspectral Imaging ◽  
Imaging System ◽  
Rapid Determination

Design of a Cooperative Chemical Agent (CA) Detection Algorithm with the Hyperspectral Imaging System

2021 ◽  
Author(s):  
Hyeong-Geun Yu ◽  
Whimin Kim ◽  
Dong-Jo Park ◽  
Dong Eui Chang ◽  
Hyunwoo Nam
Keyword(s):  
Hyperspectral Imaging ◽  
Imaging System ◽  
Detection Algorithm ◽  
Chemical Agent
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