E-mail Alert
RSS
Development of online identification system for turquoise based on hyperspectral imaging technology
-
摘要
为了避免常见的绿松石处理品及伪品入药，本文针对药用绿松石原矿样品，利用高光谱成像技术开展了绿松石在线鉴别系统的研发。依据全国各地有代表性的天然绿松石原矿样品的高分辨光谱数据，获取了标准谱线，并验证了其普适性。针对市面上常见的绿松石伪品和处理品，分析了在400 nm~1000 nm和400 nm~600 nm范围内的相关性系数的差异，探索出了实现绿松石真伪鉴别的新方法，并在此基础上构建了实验样机系统。为藏医药的矿物原材料筛选提供技术支持，促进藏医药的现代化发展。
Abstract
To prevent people from using the processed turquoise and counterfeit turquoise in medicine, this paper focuses on identifying the raw materials of medicinal turquoise. A turquoise identification system was developed using hyper-spectral imaging technology. The sample standard spectral line was obtained while the applicability was analyzed by the present sample, based on the high-resolution spectral data of ore samples from 6 representative producing areas of natural turquoise in China. A new method was summarized by the differences in correlation coefficients in the range of 400 nm~1000 nm and 400 nm~600 nm of the fake turquoise on the market and an experimental prototype system to identify the true or false of turquoise was developed. Further research will provide technical support to select raw materials in mineral medicine, which will greatly promote the modernization of Tibetan medicine.
-
Overview
Overview: Turquoise is a kind of copper-aluminum-phosphate minerals with abundant mineral reserves in China and a classic mineral medicinal material in Tibetan areas, which has excellent effects on treating wind-cold, lowering blood pressure, regulating the respiratory system and curing liver diseases. This paper focuses on identifying the raw materials of medicinal turquoise to prevent people from using the processed turquoise and counterfeit turquoise in medicine. The experimental prototype system, which can quickly and accurately pick up the true turquoise raw ore from the large amounts of fake turquoise on the market, was developed using hyper-spectral imaging technology. With the Pearson correlation between the data observed and the standard spectral line, the system was mainly composed of a control system, an optical imaging acquisition system (including the hyperspectral camera, a light source, and a darkroom), an analysis and identification system (the professional detection and analysis software) and a sorting system (the mechanical picking arm). The sample standard spectral line was obtained while the applicability was analyzed by the present sample, based on the high-resolution spectral data of ore samples from 6 representative producing areas of natural turquoise in China. A new method was summarized by the differences in correlation coefficients in the range of 400 nm~1000 nm and 400 nm~600 nm of the fake turquoise on the market. The system is going to be used to select raw materials in mineral medicine in some Tibetan medicine companies in the near future. These works will provide technical support for other research on mineral-identification, or Jewelry-identification. Further research will greatly promote the modernization of Tibetan medicine.
-
-
表 1 绿松石样品
Table 1. Turquoise samples
下载: 导出CSV
表 2 鉴别实验结果
Table 2. Identification test results
样品类别 样品数量 鉴别正确数量 鉴别错误数量 天然绿松石 100 100 0 伪品绿松石 100 100 0 沁胶过蜡绿松石 53 52 1 过蜡绿松石 52 52 0
下载: 导出CSV
-
参考文献
[1] 戴正之. 浅谈绿松石的鉴别与保养[J]. 质量与标准化, 2019(7): 30-33. doi: 10.3969/j.issn.2095-0918.2019.07.012
Dai Z Z. Discussion on the identification and maintenance of turquoise[J]. Qual Stand, 2019(7): 30-33. doi: 10.3969/j.issn.2095-0918.2019.07.012
[2] 杭东. 浅谈绿松石文化[J]. 超硬材料工程, 2013, 25(6): 57-58. doi: 10.3969/j.issn.1673-1433.2013.06.020
Hang D. Discussion on the culture of turquoise[J]. Superh Mater Eng, 2013, 25(6): 57-58. doi: 10.3969/j.issn.1673-1433.2013.06.020
[3] 才科. 二十五味松石丸治疗肝胆疾病[J]. 中国民间疗法, 2008, 16(9): 38. doi: 10.3969/j.issn.1007-5798.2008.09.038
Cai K. The treatment of liver and gall diseases with 25 kinds of songshi pills[J]. China's Naturop, 2008, 16(9): 38. doi: 10.3969/j.issn.1007-5798.2008.09.038
[4] 曲雁. "微沁"绿松石的检验[J]. 宝石和宝石学杂志, 2018, 20(5): 44-50. https://www.cnki.com.cn/Article/CJFDTOTAL-BSHB201805005.htm
Qu Y. Identification of "insignificant-filled" turquoise[J]. J Gems Gemmol, 2018, 20(5): 44-50. https://www.cnki.com.cn/Article/CJFDTOTAL-BSHB201805005.htm
[5] 陈全莉, 亓利剑, 张琰. 绿松石及其处理品与仿制品的红外吸收光谱表征[J]. 宝石和宝石学杂志, 2006, 8(1): 9-12. doi: 10.3969/j.issn.1008-214X.2006.01.003
Chen Q L, Qi L J, Zhang Y. IR Absorption spectrum representation of turquoise, treated turquoise and imitation[J]. J Gems Gemmol, 2006, 8(1): 9-12. doi: 10.3969/j.issn.1008-214X.2006.01.003
[6] 左锐, 戴慧, 蒋小平, 等. 丙烯酸酯类聚合物充填绿松石的红外光谱特征[J]. 安徽地质, 2017, 27(3): 222-224, 236. doi: 10.3969/j.issn.1005-6157.2017.03.016
Zuo R, Dai H, Jiang X P, et al. Infrared spectral features of turquoise filled with acrylic polymer[J]. Geol Anhui, 2017, 27(3): 222-224, 236. doi: 10.3969/j.issn.1005-6157.2017.03.016
[7] 徐娅芬, 狄敬如. 湖北天然绿松石与优化处理绿松石的宝石学鉴别特征[J]. 岩石矿物学杂志, 2018, 37(4): 646-654. doi: 10.3969/j.issn.1000-6524.2018.04.010
Xu Y F, Di J R. Gemological identification of natural turquoise and treatment turquoise in Hubei[J]. Acta Petrol Mineral, 2018, 37(4): 646-654. doi: 10.3969/j.issn.1000-6524.2018.04.010
[8] Schwarzinger B, Schwarzinger C. Investigation of turquoise imitations and treatment with analytical pyrolysis and infrared spectroscopy[J]. J Anal Appl Pyroly, 2017, 125: 24-31. doi: 10.1016/j.jaap.2017.05.002
[9] 闫敬文, 陈宏达, 刘蕾. 高光谱图像分类的研究进展[J]. 光学精密工程, 2019, 27(3): 680-693. https://www.cnki.com.cn/Article/CJFDTOTAL-GXJM201903023.htm
Yan J W, Chen H D, Liu L. Overview of hyperspectral image classification[J]. Opt Precis Eng, 2019, 27(3): 680-693. https://www.cnki.com.cn/Article/CJFDTOTAL-GXJM201903023.htm
[10] Zhu X Y, Li Y, Zhang Q, et al. Oil film classification using deep learning-based hyperspectral remote sensing technology[J]. ISPRS Int J Geo-Inf, 2019, 8(4): 181. doi: 10.3390/ijgi8040181
[11] 章文龙, 曾从盛, 高灯州, 等. 闽江河口湿地土壤全磷高光谱遥感估算[J]. 生态学报, 2015, 35(24): 8085-8093. doi: 10.5846/stxb201406241303
Zhang W L, Zeng C S, Gao D Z, et al. Estimating the soil total phosphorus content based on hyper-spectral remote sensing data in the Min River estuarine wetland[J]. Acta Ecol Sin, 2015, 35(24): 8085-8093. doi: 10.5846/stxb201406241303
[12] Ren Z L, Sun L, Zhai Q P. Improved k-means and spectral matching for hyperspectral mineral mapping[J]. Int J Appl Earth Obs Geoinformation, 2020, 91: 102154. doi: 10.1016/j.jag.2020.102154
[13] 郭文川, 董金磊. 高光谱成像结合人工神经网络无损检测桃的硬度[J]. 光学精密工程, 2015, 23(6): 1530-1537. doi: 10.3788/OPE.20152306.1530
Guo W C, Dong J L. Nondestructive detection on firmness of peaches based on hyperspectral imaging and artificial neural networks[J]. Opt Precis Eng, 2015, 23(6): 1530-1537. doi: 10.3788/OPE.20152306.1530
[14] 张成业, 秦其明, 陈理, 等. 高光谱遥感岩矿识别的研究进展[J]. 光学精密工程, 2015, 23(8): 2407-2418. https://www.cnki.com.cn/Article/CJFDTOTAL-GXJM201508036.htm
Zhang C Y, Qin Q M, Chen L, et al. Research and development of mineral identification utilizing hyperspectral remote sensing[J]. Opt Precis Eng, 2015, 23(8): 2407-2418. https://www.cnki.com.cn/Article/CJFDTOTAL-GXJM201508036.htm
[15] 贺佳, 刘冰锋, 李军. 不同生育时期冬小麦叶面积指数高光谱遥感监测模型[J]. 农业工程学报, 2014, 30(24): 141-150. doi: 10.3969/j.issn.1002-6819.2014.24.017
He J, Liu B F, Li J. Monitoring model of leaf area index of winter wheat based on hyperspectral reflectance at different growth stages[J]. Trans Chin Soc Agric Eng, 2014, 30(24): 141-150. doi: 10.3969/j.issn.1002-6819.2014.24.017
[16] 张雷蕾, 李永玉, 彭彦昆, 等. 基于高光谱成像技术的猪肉新鲜度评价[J]. 农业工程学报, 2012, 28(7): 254-259. doi: 10.3969/j.issn.1002-6819.2012.07.042
Zhang L L, Li Y Y, Peng Y K, et al. Determination of pork freshness attributes by hyperspectral imaging technique[J]. Trans Chin Soc Agric Eng, 2012, 28(7): 254-259. doi: 10.3969/j.issn.1002-6819.2012.07.042
[17] 单佳佳, 彭彦昆, 王伟, 等. 基于高光谱成像技术的苹果内外品质同时检测[J]. 农业机械学报, 2011, 42(3): 140-144. doi: 10.3969/j.issn.1000-1298.2011.03.027
Shan J J, Peng Y K, Wang W, et al. Simultaneous detection of external and internal quality parameters of apples using hyperspectral technology[J]. Trans Chin Soc Agric Mach, 2011, 42(3): 140-144. doi: 10.3969/j.issn.1000-1298.2011.03.027
[18] 樊嵘, 孟大志, 徐大舜. 统计相关性分析方法研究进展[J]. 数学建模及其应用, 2014, 3(1): 1-12. doi: 10.3969/j.issn.2095-3070.2014.01.002
Fan R, Meng D Z, Xu D S. Survey of research process on statistical correlation analysis[J]. Math Model Appl, 2014, 3(1): 1-12. doi: 10.3969/j.issn.2095-3070.2014.01.002
[19] 闻兵工, 冯伍法, 刘伟, 等. 基于光谱曲线整体相似性测度的匹配分类[J]. 测绘科学技术学报, 2009, 26(2): 128-131. doi: 10.3969/j.issn.1673-6338.2009.02.014
Wen B G, Feng W F, Liu W, et al. Matching and classification based on the whole comparability measure of spectral curve[J]. J Geomat Sci Technol, 2009, 26(2): 128-131. doi: 10.3969/j.issn.1673-6338.2009.02.014
[20] 杨甲森. 卫星遥测数据相关性知识发现方法研究[D]. 北京: 中国科学院大学(中国科学院国家空间科学中心), 2019.
Yang J S. Research on correlation knowledge discovery method of spacecraft telemetry data[D]. Beijing: University of Chinese Academy of Sciences (National Space Science Center, the Chinese Academy of Sciences), 2019.
[21] 赵虹霞, 伏修锋, 干福熹, 等. 不同产地绿松石无损检测及岩相结构特征研究[J]. 岩矿测试, 2007, 26(2): 141-144. doi: 10.3969/j.issn.0254-5357.2007.02.015
Zhao H X, Fu X F, Gan F X, et al. Study on mineralogical characteristics of turquoise samples from different provenances by non-destructive analysis[J]. Rock Mineral Anal, 2007, 26(2): 141-144. doi: 10.3969/j.issn.0254-5357.2007.02.015
[22] 王戬. 基于ICP-MS和XRD的绿松石原矿真伪检测[D]. 武汉: 中南民族大学, 2019.
Wang J. Detection of the authenticity of turquoise raw ore based on ICP-MS and XRD[D]. Wuhan: South-Central Minzu University, 2019.
[23] 方圣辉, 龚浩. 动态调整权重的光谱匹配测度法分类的研究[J]. 武汉大学学报·信息科学版, 2006, 31(12): 1044-1046. doi: 10.3321/j.issn:1671-8860.2006.12.003
Fang S H, Gong H. Spectral simil arity scale based on dynamic wighting adjustment method[J]. Geomat Inf Sci Wuhan Univ, 2006, 31(12): 1044-1046. doi: 10.3321/j.issn:1671-8860.2006.12.003
-
访问统计
点击扫一扫
图(8)
表(2)
计量
- 文章访问数:
- PDF下载数:
- 施引文献: 0
