Spectroscopy and Spectral Analysis, Volume. 41, Issue 9, 2892(2021)
Non-Destructive Identification of Hazardousbone Fragments Embedded in the Frozen-Thawed Pork Based on Multispectral Imaging
Figures & Tables(8)
Fig. 1. Flow chart of the identification of FT-LPS-BFs based on MSI technology
Fig. 3. Two-dimensional scatter plots of PCA by using (a) ROIs-1 full spectra, (b) ROIs-2 full spectra and (c) ROIs-2 key spectra
Fig. 4. Images of typical samples in SVM models based on image information
Table 1. Size of bone fragments
View tableView in ArticleTable 1. Size of bone fragments
特征 最小值 最大值 均值 标准差 长度/cm 1.15 2.56 1.71 0.50 厚度/cm 0.16 0.58 0.28 0.11
Table 2. Performance parameters of SVM and NN models based on (Ⅰ) ROIs-1 full spectra, (Ⅱ) ROIs-2 full spectra and (Ⅲ) ROIs-2 key spectra
View tableView in ArticleTable 2. Performance parameters of SVM and NN models based on (Ⅰ) ROIs-1 full spectra, (Ⅱ) ROIs-2 full spectra and (Ⅲ) ROIs-2 key spectra
类型 分类模型 样品 训练集 测试集 准确率
/%灵敏度 精确率 特异性 灵敏度 精确率 特异性 Ⅰ SVM FT-LPS 0.84 0.89 0.95 0.47 0.41 0.67 55.56 FT-LPS-SBF 0.96 0.84 0.91 0.47 0.78 0.93 FT-LPS-IBF 0.78 0.85 0.93 0.73 0.58 0.73 NN FT-LPS 0.98 0.99 0.98 0.70 0.75 0.54 71 FT-LPS-SBF 0.96 0.96 0.92 0.55 0.96 0.86 FT-LPS-IBF 0.93 0.99 0.98 0.85 0.86 0.79 Ⅱ SVM FT-LPS 1.00 1.00 1.00 1.00 1.00 1.00 100 FT-LPS-SBF 1.00 1.00 1.00 1.00 1.00 1.00 FT-LPS-IBF 1.00 1.00 1.00 1.00 1.00 1.00 NN FT-LPS 1.00 1.00 1.00 1.00 1.00 1.00 100 FT-LPS-SBF 1.00 1.00 1.00 1.00 1.00 1.00 FT-LPS-IBF 1.00 1.00 1.00 1.00 1.00 1.00 Ⅲ SVM FT-LPS 0.98 1.00 1.00 1.00 1.00 1.00 100 FT-LPS-SBF 0.98 1.00 1.00 1.00 1.00 1.00 FT-LPS-IBF 1.00 0.96 0.98 1.00 1.00 1.00 NN FT-LPS 1.00 1.00 1.00 1.00 0.88 0.93 100 FT-LPS-SBF 1.00 1.00 1.00 1.00 1.00 1.00 FT-LPS-IBF 1.00 1.00 1.00 0.87 1.00 1.00
Table 3. Confusion matrixes of SVM and NN models for the classification of FT-LPS and FT-LPS-BFs based on key wavelengths
View tableView in ArticleTable 3. Confusion matrixes of SVM and NN models for the classification of FT-LPS and FT-LPS-BFs based on key wavelengths
模型 真实类 训练集 测试集 总精度/% FT-LPS FT-LPS-BF FT-LPS FT-LPS-BF SVM FT-LPS 49 1 15 0 100 FT-LPS-BF 0 100 0 30 NN FT-LPS 50 0 15 0 95.56 FT-LPS-BF 0 100 2 28
Table 4. Results of SVM and NN models based on image information
View tableView in ArticleTable 4. Results of SVM and NN models based on image information
模型 真实样品 判别结果 灵敏
度精确
率特异
性总精度
/%FT-LPS FT-LPS-BF SVM FT-LPS 59 6 0.91 0.91 0.95 93.8 FT-LPS-BF 6 124 0.95 0.95 0.91 NN FT-LPS 59 6 0.91 0.89 0.95 93.33 FT-LPS-BF 7 123 0.95 0.95 0.91
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Hua-feng ZHANG, Wu WANG, Yu-rong BAI, Yi-ru LIU, Tao JIN, Xia YU, Fei MA. Non-Destructive Identification of Hazardousbone Fragments Embedded in the Frozen-Thawed Pork Based on Multispectral Imaging[J]. Spectroscopy and Spectral Analysis, 2021, 41(9): 2892
Paper Information
Category: Research Articles
Received: Jun. 2, 2020
Accepted: --
Published Online: Oct. 29, 2021
The Author Email: ZHANG Hua-feng (545175746@qq.com)
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