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Color Discrimination Based on Hyperspectral Imaging Method |
YE Qi1,2, WANG Yue-ming1*, ZHOU Shi-yao1,2, CHENG Xiao-yu1,2, JIA Jian-xin1,2 |
1. Key Laboratory of Space Active Opto-Electronics Technology, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China
2. University of Chinese Academy of Sciences, Beijing 100049, China |
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Abstract It is very difficult to distinguish samples with similar colors in color measurement. Accuracy and efficiency are very important for industries’ application. A method for color measurement based on hyper- spectral imaging technology was proposed, and a prototype was integrated in this paper. The system is able to measure the spectrum of the colorful samples rapidly. The color analysis or color coordinates were calculated after measurement. This method provided the image and spectrum at the same time. To evaluate the performance of the system, analysis and experiment were also performed. We compared the signal-to-noise ratio of each bands that are subdivided, and used the spectral mapping technique to compare the advantages and disadvantages of the color cameras and the proposed system. The results show that we proposed a more accurate method for color measurement and it can test the quality of products efficiently.
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Received: 2017-09-28
Accepted: 2018-01-28
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Corresponding Authors:
WANG Yue-ming
E-mail: wangym@mail.sitp.ac.cn
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[1] Wyszecki G,Stiles W. Color Science: Concepts and Methods, Quantitative Data and Formulas. 2th Edition, Wiley, New York, 1982.
[2] Katranilk J, Pernu F, Likar B. Optics Express, 2013, 21(4): 4841.
[3] Casasent D P. Proc SPIE, 1999, 50(50): 117.
[4] Goudail F, Roux N, Baarstad I, et al. Applied Optics, 2006, 45(21): 5223.
[5] Xu H Y, Wang Q Q, Sun Y L. Proc. SPIE, 2003, 5293: 27.
[6] Žiga Špiclin, Jaka Katranik, Miran Bürmen, et al. Applied Optics, 2010, 49(15): 2813.
[7] Chai Sek M, Gentile Antonio, Lugo-Beauchamp Wilfredo E, et al. Applied Optics, 2000, 39(5): 835.
[8] Brito R S, Pinheiro H M, Ferreira F, et al. Applied Spectroscopy, 2016, 70(3): 443.
[9] Eran Bahalul, Asaf Bronfeld, Shlomi Epshtein, et al. Optics Letters, 2016, 41(5): 938.
[10] Wei L, Xiao X, Wang Y, et al. Infrared Physics & Technology, 2017, 86.
[11] Liu P, Zhao N, Ren L H, et al. Chinese Optics Letters, 2014, 12(A01): 98.
[12] Ishikawa D, Motomura A, Igarashi Y, et al. Spectroscopy and Spectral Analysis, 2015, 35(4): 865.
[13] Jia J, Wang Y, Zhuang X, et al. Infrared Physics & Technology, 2017, 81: 305.
[14] Wang Y M, Xie F, Wang J Y. Chinese Optics Letters, 2016,(12): 132.
[15] Levent Baayigit, Mert Dedeoglu, Hseyin Akgl, et al. Spectroscopy and Spectral Analysis, 2017,37(1): 293. |
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