基于光谱数据融合技术的手帕纸品牌分类
Classification of Handkerchief Paper Brand Based on Spectral Data Fusion Technology
图 & 表
图 1. 手帕纸样本的红外光谱
Fig. 1. Infrared spectra of handkerchief paper samples
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图 2. 手帕纸样本的拉曼光谱
Fig. 2. Raman spectra of handkerchief paper samples
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图 3. 8个品牌手帕纸在不同维度下分类准确率的变化趋势图
Fig. 3. Trend chart of classification accuracy of 8 brands of handkerchief paper in different dimensions
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图 4. 14个系列心相印手帕纸在不同维度下的分类准确率
Fig. 4. Classification accuracy of 14 series of Xinxiangyin handkerchiefs in different dimensions
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表 1两种光谱线性判别分析的准确率、召回率和假正率
Table1. LDA accuracy, recall rate and false positive rate of two spectra
Brand | Infrared spectrum | Raman spectrum |
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Accuracy/% | Recall/% | False positive/% | Accuracy/% | Recall/% | False positive/% |
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QF | 92.1 | 66.7 | 5.3 | 96.8 | 66.7 | 0 | SJ | 85.7 | 66.7 | 11.1 | 98.4 | 88.9 | 0 | WD | 92.1 | 66.7 | 2.0 | 88.9 | 66.7 | 5.9 | XBB | 92.1 | 55.6 | 1.9 | 93.7 | 77.8 | 3.7 | XS | 90.5 | 83.3 | 8.8 | 93.7 | 83.3 | 5.3 | XXY | 92.1 | 77.8 | 5.6 | 90.5 | 77.8 | 7.4 | XZL | 93.7 | 66.7 | 3.5 | 98.4 | 83.3 | 0.0 | YR | 92.1 | 33.3 | 1.8 | 98.4 | 100 | 1.8 |
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表 2光谱融合后线性判别分析的准确率、召回率和假正率
Table2. LDA accuracy, recall rate and false positive rate after spectral fusion
Brand | Accuracy/% | Recall/% | False positive/% |
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QF | 98.4 | 83.3 | 0 | SJ | 98.4 | 88.9 | 0 | WD | 92.1 | 75.0 | 3.9 | XBB | 95.2 | 88.9 | 3.7 | XS | 95.2 | 83.3 | 3.5 | XXY | 93.7 | 88.9 | 5.6 | XZL | 98.4 | 83.3 | 0 | YR | 96.8 | 83.3 | 1.8 |
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表 3主成分分析的特征方差贡献率
Table3. Characteristic variance contribution rate of PCA
Component | Eigenvalue | Variance/% | Cumulative variance/% | | Component | Eigenvalue | Variance/% | Cumulative variance/% |
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PC1 | 437.789 | 48.162 | 48.162 | | PC20 | 2.176 | 0.239 | 96.066 | PC2 | 231.312 | 25.447 | 73.608 | | PC21 | 2.096 | 0.231 | 96.297 | PC3 | 90.879 | 9.998 | 83.606 | | PC22 | 2.023 | 0.223 | 96.520 | PC4 | 26.028 | 2.863 | 86.470 | | PC23 | 1.918 | 0.211 | 96.731 | PC5 | 21.176 | 2.330 | 88.799 | | PC24 | 1.786 | 0.196 | 96.927 | PC6 | 11.269 | 1.240 | 90.039 | | PC25 | 1.702 | 0.187 | 97.114 | PC7 | 8.257 | 0.908 | 90.947 | | PC26 | 1.587 | 0.175 | 97.289 | PC8 | 6.497 | 0.715 | 91.662 | | PC27 | 1.481 | 0.163 | 97.452 | PC9 | 5.023 | 0.553 | 92.215 | | PC28 | 1.425 | 0.157 | 97.609 | PC10 | 4.111 | 0.452 | 92.667 | | PC29 | 1.382 | 0.152 | 97.761 | PC11 | 4.000 | 0.440 | 93.107 | | PC30 | 1.289 | 0.142 | 97.902 | PC12 | 3.757 | 0.413 | 93.520 | | PC31 | 1.252 | 0.138 | 98.040 | PC13 | 3.719 | 0.409 | 93.929 | | PC32 | 1.183 | 0.130 | 98.170 | PC14 | 3.475 | 0.382 | 94.311 | | PC33 | 1.154 | 0.127 | 98.297 | PC15 | 3.178 | 0.350 | 94.661 | | PC34 | 1.089 | 0.12 | 98.417 | PC16 | 3.035 | 0.334 | 94.995 | | PC35 | 1.024 | 0.113 | 98.530 | PC17 | 2.756 | 0.303 | 95.298 | | PC36 | 0.952 | 0.105 | 98.634 | PC18 | 2.507 | 0.276 | 95.574 | | PC37 | 0.914 | 0.101 | 98.735 | PC19 | 2.300 | 0.253 | 95.827 | | | | | |
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表 4线性判别分析在不同维度下的准确率
Table4. Accuracy of LDA in different dimensions
Dimension | Precision/% | Overall accuracy/% |
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QF | SJ | WD | XS | XBB | XXY | XZL | YR |
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2 | 50.0 | 11.1 | 0 | 55.6 | 33.3 | 11.1 | 66.7 | 0 | 25.4 | 3 | 83.3 | 55.6 | 8.3 | 44.4 | 66.7 | 33.3 | 66.7 | 16.7 | 42.9 | 4 | 83.3 | 66.7 | 16.7 | 44.4 | 66.7 | 33.3 | 66.7 | 16.7 | 46.0 | 5 | 83.3 | 44.4 | 33.3 | 55.6 | 66.7 | 44.4 | 66.7 | 16.7 | 49.2 | 6 | 83.3 | 33.3 | 25.0 | 55.6 | 66.7 | 55.6 | 83.3 | 33.3 | 50.8 | 7 | 83.3 | 33.3 | 50.0 | 66.7 | 66.7 | 66.7 | 83.3 | 33.3 | 58.7 | 8 | 83.3 | 44.4 | 50.0 | 77.8 | 66.7 | 66.7 | 83.3 | 33.3 | 61.9 | 9 | 83.3 | 44.4 | 58.3 | 77.8 | 66.7 | 66.7 | 83.3 | 33.3 | 63.5 | 10 | 83.3 | 55.6 | 58.3 | 77.8 | 83.3 | 66.7 | 83.3 | 50.0 | 68.3 | 11 | 100 | 66.7 | 58.3 | 77.8 | 100 | 66.7 | 66.7 | 66.7 | 73.0 | 12 | 100 | 44.4 | 50.0 | 66.7 | 100 | 77.8 | 66.7 | 66.7 | 68.3 | 13 | 100 | 44.4 | 66.7 | 66.7 | 100 | 100 | 66.7 | 83.3 | 76.2 | 14 | 83.3 | 66.7 | 66.7 | 77.8 | 83.3 | 100 | 66.7 | 66.7 | 76.2 | 15 | 83.3 | 66.7 | 75.0 | 77.8 | 83.3 | 100 | 66.7 | 66.7 | 77.8 | 16 | 83.3 | 77.8 | 66.7 | 88.9 | 83.3 | 88.9 | 66.7 | 50.0 | 76.2 | 17 | 100 | 88.9 | 66.7 | 88.9 | 83.3 | 88.9 | 66.7 | 83.3 | 82.5 | 18 | 100 | 100 | 83.3 | 88.9 | 100 | 100 | 100 | 83.3 | 93.7 | 19 | 100 | 100 | 91.7 | 88.9 | 100 | 88.9 | 83.3 | 100 | 93.7 | 20 | 100 | 100 | 83.3 | 77.8 | 100 | 88.9 | 100 | 100 | 92.1 | 21 | 100 | 100 | 83.3 | 88.9 | 100 | 88.9 | 83.3 | 100 | 92.1 | 22 | 100 | 100 | 83.3 | 88.9 | 100 | 100 | 100 | 100 | 95.2 | 23 | 100 | 88.9 | 83.3 | 88.9 | 100 | 100 | 100 | 100 | 93.7 | 24 | 100 | 100 | 75.0 | 88.9 | 100 | 100 | 100 | 100 | 93.7 | 25 | 100 | 100 | 83.3 | 88.9 | 100 | 100 | 100 | 100 | 95.2 | 26 | 100 | 100 | 91.7 | 88.9 | 100 | 100 | 100 | 100 | 96.8 | 27 | 100 | 100 | 91.7 | 88.9 | 100 | 100 | 100 | 100 | 96.8 | 28 | 100 | 100 | 91.7 | 88.9 | 100 | 100 | 100 | 100 | 96.8 | 29 | 100 | 100 | 91.7 | 88.9 | 100 | 100 | 100 | 100 | 96.8 | 30 | 100 | 100 | 91.7 | 88.9 | 100 | 100 | 100 | 100 | 96.8 | 31 | 100 | 100 | 100 | 88.9 | 100 | 100 | 100 | 100 | 98.4 | 32 | 100 | 100 | 100 | 88.9 | 100 | 100 | 100 | 100 | 98.4 | 33 | 100 | 100 | 100 | 88.9 | 100 | 100 | 100 | 100 | 98.4 | 34 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 |
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表 5检材与样本的比对结果
Table5. Comparison results of material and sample
Material | QF | SJ | WD | XS | XBB | XXY | XZL | YR |
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JC1 | | | | | | √ | | | JC2 | | | √ | | | | | |
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季佳华, 王继芬, 何欣龙. 基于光谱数据融合技术的手帕纸品牌分类[J]. 激光与光电子学进展, 2021, 58(3): 0330004. Ji Jiahua, Wang Jifen, He Xinlong. Classification of Handkerchief Paper Brand Based on Spectral Data Fusion Technology[J]. Laser & Optoelectronics Progress, 2021, 58(3): 0330004.