• Spectroscopy and Spectral Analysis
  • Vol. 42, Issue 9, 2903 (2022)
Zhen-qing ZHANG1、*, Li-juan DONG2、2; *;, Yu HUANG4、4;, Xing-hai CHEN4、4;, Wei HUANG5、5;, and Yong SUN6、6;
Author Affiliations
  • 11. Department of Criminal Science and Technology, Railway Police College, Zhengzhou 450053, China
  • 22. Shanxi Provincial Key Laboratory of Microstructure Electromagnetic Functional Materials, Shanxi Datong University, Datong 037009, China
  • 44. Wuxi Spectrum Vision Technology Co., Ltd., Wuxi 214000, China
  • 55. Institute of Forensic Science, Ministry of Public Security, Beijing 100038, China
  • 66. MOE Key Laboratory of Advanced Micro-Structured Materials, School of Physics Science and Engineering, Tongji University, Shanghai 200092, China
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    DOI: 10.3964/j.issn.1000-0593(2022)09-2903-10 Cite this Article
    Zhen-qing ZHANG, Li-juan DONG, Yu HUANG, Xing-hai CHEN, Wei HUANG, Yong SUN. Identification of True and Counterfeit Banknotes Based on Hyperspectral Imaging[J]. Spectroscopy and Spectral Analysis, 2022, 42(9): 2903 Copy Citation Text show less
    GaiaSorter hyperspectral sorter
    Fig. 1. GaiaSorter hyperspectral sorter
    Three-dimensional perspective views of the front and back of 100 yuan RMB
    Fig. 2. Three-dimensional perspective views of the front and back of 100 yuan RMB
    Spectral reflectance curves of the characteristic points on the front and back of real and counterfeit 100 yuan RMB banknotes
    Fig. 3. Spectral reflectance curves of the characteristic points on the front and back of real and counterfeit 100 yuan RMB banknotes
    The grayscale images of the front and back of the real and counterfeit 100 yuan RMB banknotes at 500, 660 and 870 nm
    Fig. 4. The grayscale images of the front and back of the real and counterfeit 100 yuan RMB banknotes at 500, 660 and 870 nm
    The grayscale images of the real and counterfeit 100 yuan RMB based on band operation
    Fig. 5. The grayscale images of the real and counterfeit 100 yuan RMB based on band operation
    The first 12 principal components for the front sides of the real and counterfeit 100 yuan RMB
    Fig. 6. The first 12 principal components for the front sides of the real and counterfeit 100 yuan RMB
    The first 12 principal components for the back sides of the real and counterfeit 100 yuan RMB
    Fig. 7. The first 12 principal components for the back sides of the real and counterfeit 100 yuan RMB
    The texture informations of the grayscale images of the back sides of the real and counterfeit banknotes at 550 nmFrom left to right are the mean, variance, inverse difference moment, contrast, dissimilarity, entropy, angle second-order moment, correlations, respectively
    Fig. 8. The texture informations of the grayscale images of the back sides of the real and counterfeit banknotes at 550 nm
    From left to right are the mean, variance, inverse difference moment, contrast, dissimilarity, entropy, angle second-order moment, correlations, respectively
    The texture informations of the grayscale images of the front sides of the real and counterfeit banknotes at 550 nmFrom left to right are the mean, variance, inverse difference moment, contrast, dissimilarity, entropy, angle second-order moment, correlations, respectively
    Fig. 8. The texture informations of the grayscale images of the front sides of the real and counterfeit banknotes at 550 nm
    From left to right are the mean, variance, inverse difference moment, contrast, dissimilarity, entropy, angle second-order moment, correlations, respectively
    序号名称作用
    1均值反映了灰度的平均情况
    2方差反映了灰度变化的大小
    3逆差矩反映了局部同质性, 当共生矩阵沿对角线集中时, 其值较大
    4对比度反映了影响纹理的清晰度
    5非相似度与对比度相同, 用来检测相似性
    6是图像所具有的信息量的度量
    7角二阶矩反映了图像灰度分布的均匀性
    8相关性反映某种灰度值沿某个方向的延伸长度
    Table 1. Texture features and its effect based on gray level co-occurrence matrix
    Zhen-qing ZHANG, Li-juan DONG, Yu HUANG, Xing-hai CHEN, Wei HUANG, Yong SUN. Identification of True and Counterfeit Banknotes Based on Hyperspectral Imaging[J]. Spectroscopy and Spectral Analysis, 2022, 42(9): 2903
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