|
|
|
|
|
|
| Study on Detection Method of Foxing on Paper Artifacts Based on
Hyperspectral Imaging Technology |
| DAI Ruo-chen1, TANG Huan2*, TANG Bin1*, ZHAO Ming-fu1, DAI Li-yong1, ZHAO Ya3, LONG Zou-rong1, ZHONG Nian-bing1 |
1. Chongqing Key Laboratory of Fiber Optic Sensor and Photodetector，Chongqing University of Technology, Chongqing 400054，China
2. Key Scientific Research Base of Pest and Mold Control of Museum Collections of National Cultural Heritage Administration, Chongqing China Three Gorges Museum, Chongqing 400015, China
3. Chongqing University of Education，Chongqing 400065，China
|
|
|
|
|
Abstract Affected by preservation conditions, foxing will form on the surface of many paper cultural relics. If effective monitoring and scientific judgment are not carried out, the safety of paper cultural relics will be further affected. For the detection of foxing disease on paper cultural relics, there are problems such as hysteresis and subjectivity. It is difficult to identify the area covered by ink, paint and seals in the painting and calligraphy collection. Therefore, the concept of preventive protection based on cultural relics needs to be developed urgently. Non-destructive testing technology for efficient and accurate identification of foxing. The visible-near-infrared hyperspectral image combines spectrum and image, contains rich spatial information and spectral information, and can achieve lossless batch collection of sample spectral information on the flat. This research proposes a rapid identification method based on hyperspectral imaging technology to detect foxing on paper cultural relics. Obtain hyperspectral images of simulating paper cultural relics at the 360～970 nm. Because the 360～450 nm image is much affected by noise, we choose to exclude this part of the spectral data; select the region of interest, obtain the corresponding average spectral reflectivity, and compare the healthy area with that. In the area of foxing infection, it is found that there is a difference in the spectral curves of the two; near 450～600 nm, the spectral reflectivity of the affected area of foxing is higher than that of the healthy area, and the peak shape appears near 600 nm; and in the range of 600～900 nm, The spectrum of the infected area and the healthy area tends to be stable, and the difference between the two gradually decreases. Select the feature information extracted from the image corresponding to the feature wavelength to build an image recognition model, using band math to observe the image characteristics of foxing, the size and distribution of the foxing can be displayed, but the overlapping parts with the seal and ink, the foxing are covered by the seal and ink, which is difficult to identify; use the minimum noise fraction, although different parts are overlapping, it can find hidden foxing that is difficult to identify with the naked eye; 180 pieces of hyperspectral data (450～970 nm) establish a foxing discrimination model, randomly divided into 120 pieces of data as the training set, and 60 pieces of data as the test set, K-nearest neighbor method and BP neural network are used to establish a paper cultural relics foxing spectrum discrimination model. In general, the two methods have distinguished rates of 73.3% and 85% respectively; Comparing with the K-nearest neighbor model, the BP neural network has a higher overall discrimination rate and a better recognition effect. The results show that hyperspectral imaging can efficiently and accurately identify the foxing of paper cultural relics, provide reliable technical means for the follow-up research on the distribution and development of foxing, and provide guidance for the preservation of cultural relics in the museum.
|
|
Received: 2021-04-13
Accepted: 2021-07-27
|
|
|
|
Corresponding Authors:
TANG Huan, TANG Bin
E-mail: tanghuan3gm@163.com；tangbin@cqut.edu.cn
|
|
[1] Szulc J, Otlewska A, Ruman T, et al. International Biodeterioration & Biodegradation, 2018, 132: 157.
[2] CHEN Hui-qiong（陈惠琼）. Archives Science Bulletin（档案学通讯），2018，(5)：81.
[3] Sclocchi M C，Kraková L，Pinzari F，et al. Microbial Ecology，2017，73(4)：815.
[4] XIE Yan（谢 燕）. Sciences of Conservation and Archaeology（文物保护与考古科学）, 2010，(3)：86.
[5] WU Wang-ting，ZHANG Chen-feng，GAO Ai-dong，et al（武望婷，张陈锋，高爱东，等）. Sciences of Conservation and Archaeology（文物保护与考古科学），2017，29(4)：45.
[6] ZHOU Xin-guang，CHU Hao，WU Lai-ming（周新光, 褚 昊, 吴来明）. Sciences of Conservation and Archaeology（文物保护与考古科学），2020，32(3)：65.
[7] WU Feng-qiang，YANG Wu-nian，LI Dan（武锋强, 杨武年, 李 丹）. Acta Mineralogica Sinica（矿物学报），2014，34(2)：166.
[8] Zhang M，Li C，Yang F. Computers and Electronics in Agriculture，2017，139：75.
[9] Bagnasco L，Zotti M，Sitta N，et al. Talanta，2015，144：1225.
[10] Kang X, Xiang X, Li S, et al. IEEE Transactions on Geoscience & Remote Sensing, 2017, 55(12): 7140.
[11] ZHANG Jing-yi，CHEN Jin-chao，FU Xia-ping，et al（张静宜，陈锦超，傅霞萍，等）. Spectroscopy and Spectral Analysis（光谱学与光谱分析），2019，39(10)：3184.
[12] Ye Chengming，Liu Xin，Xu Hong，et al. Journal of Zhejiang University-Science A (Applied Physics & Engineering)，2020，21(3)：240.
[13] Li J B, Huang W Q, Tian X, et al. Computers & Electronics in Agriculture, 2015, 127: 582.
|
| [1] |
LI Jia-wang, LIU Yan, ZHANG De-qing, YANG Yong-an, ZHANG Chuan-yun, LI Lun, SI Min-zhen*. Comparison and Analysis of IR Spectra of Four Dendrobium Species[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(10): 2989-2994. |
| [2] |
SHI Dong-dong, CAO Zhao-bin, HUAN Yan-hua, GONG Yan-chun, WU Wen-yuan, YANG Jun*. Reflection Polarization Spectral Characteristics of High Performance Coating Material La2Zr2O7[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(10): 2995-2999. |
| [3] |
LIAO Yi-min1, YAN Yin-zhou1, WANG Qiang2*, YANG Li-xue3, PAN Yong-man1, XING Cheng1, JIANG Yi-jian1, 2. Laser-Induced Growth Device and Optical Properties of ZnO
Microcrystals[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(10): 3000-3005. |
| [4] |
YANG Kun, CHEN Lei*, CHENG Fan-chong, PEI Huan, LIU Gui-ming, WANG Bao-huai, ZENG Wen. Emission Spectroscopy Diagnosis of Air Gliding Arc Plasma Under
Atmospheric Pressure Condition[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(10): 3006-3011. |
| [5] |
ZHU Gui-jun, WANG Gan-zhen, PENG Jun*, TIAN Zong-ping, HOU Zhi-hua. The Mineralogical and Spectroscopic Characteristics of Phosphohedyphane From Chenzhou of Hunan Province[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(10): 3017-3023. |
| [6] |
LEI Bing-ying1, 2, XU Bo-ping1, 2, WANG Yi-shan1, 2, ZHU Xiang-ping1, 2, DUAN Yi-xiang3, ZHAO Wei1, 2, TANG Jie1*. Investigation of the Spectral Characteristics of Laser-Induced Plasma for Non-Flat Samples[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(10): 3024-3030. |
| [7] |
ZHANG Yong-bin1, ZHU Dan-dan1, CHEN Ying1*, LIU Zhe1, DUAN Wei-liang1, LI Shao-hua2. Wavelength Selection Method of Algal Fluorescence Spectrum Based on Convex Point Extraction From Feature Region[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(10): 3031-3038. |
| [8] |
ZHENG Yu-xia1, 2, TUERSUN Paerhatijiang1, 2*, ABULAITI Remilai1, 2, CHENG Long1, 2, MA Deng-pan1, 2. Retrieval of Polydisperse Au-Ag Alloy Nanospheres by Spectral Extinction Method[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(10): 3039-3045. |
| [9] |
JIN Cheng-qian1, 2, GUO Zhen1, ZHANG Jing1, MA Cheng-ye1, TANG Xiao-han1, ZHAO Nan1, YIN Xiang1. Non-Destructive Detection and Visualization of Soybean Moisture Content Using Hyperspectral Technique[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(10): 3052-3057. |
| [10] |
CAO Yu-qi2, KANG Xu-sheng1, 2*, CHEN Piao-yun2, XIE Chen2, YU Jie2*, HUANG Ping-jie2, HOU Di-bo2, ZHANG Guang-xin2. Research on Discrimination Method of Absorption Peak in Terahertz
Regime[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(10): 3058-3062. |
| [11] |
QI Dong-li, CHENG Jia, SUN Hui, ZHANG Rui-xin, SONG Jian-yu, QIN Yan-li, LI Hong-da, SHEN Long-hai*. Research on Spectral Characteristics and Photocatalytic Properties of Ball Milled TiO2[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(10): 3063-3067. |
| [12] |
LI Yuan1, ZHANG Wen-bo1, CHEN Xiao-lin2, 3, LI Han1, ZHANG Guan-jun1. Application of Gaussian Process Regression on the Quantitative Analysis of the Aging Condition of Insulating Paper by Near-Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(10): 3073-3078. |
| [13] |
WU Bin1, SHEN Jia-qi2, WANG Xin2, WU Xiao-hong3, HOU Xiao-lei2. NIR Spectral Classification of Lettuce Using Principal Component
Analysis Sort and Fuzzy Linear Discriminant Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(10): 3079-3083. |
| [14] |
WANG Xu-yang1, SUN Tao1, ZHU Xin-ping1, TANG Guang-mu2, JIA Hong-tao1*, XU Wan-li2. Phosphorus Species of Biochar Modified by Phosphoric Acid and
Pyrophosphoric Acid Based on Spectral Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(10): 3084-3090. |
| [15] |
YAN Peng-cheng1, 2, ZHANG Xiao-fei2*, SHANG Song-hang2, ZHANG Chao-yin2. Research on Mine Water Inrush Identification Based on LIF and
LSTM Neural Network[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(10): 3091-3096. |
|
|
|
|
