Abstract

To improve the classification accuracy of laser-induced breakdown spectroscopy (LIBS), image histogram of oriented gradients (HOG) features method (IHFM) for materials analysis was proposed in this work. 24 rice (Oryza sativa L.) samples were carried out to verify the proposed method. The results showed that the classification accuracy of rice samples by the full-spectra intensities method (FSIM) and IHFM were 60.25% and 81.00% respectively. The classification accuracy was obviously improved by 20.75%. Universality test results showed that this method also achieved good results in the plastics, steel, rock and minerals classification. This study provides an effective method to improve the classification performance of LIBS.

© 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

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  1. Z. Chen, H. Li, M. Liu, and R. Li, “Fast and sensitive trace metal analysis in aqueous solutions by laser-induced breakdown spectroscopy using wood slice substrates,” Spectrochim. Acta B At. Spectrosc. 63(1), 64–68 (2008).
    [Crossref]
  2. R. Yi, X. Yang, R. Zhou, J. Li, H. Yu, Z. Hao, L. Guo, X. Li, Y. Lu, and X. Zeng, “Determination of Trace Available Heavy Metals in Soil Using Laser-Induced Breakdown Spectroscopy Assisted with Phase Transformation Method,” Anal. Chem. 90(11), 7080–7085 (2018).
    [Crossref] [PubMed]
  3. C. Li, Z. Hao, Z. Zou, R. Zhou, J. Li, L. Guo, X. Li, Y. Lu, and X. Zeng, “Determinations of trace boron in superalloys and steels using laser-induced breakdown spectroscopy assisted with laser-induced fluorescence,” Opt. Express 24(8), 7850–7857 (2016).
    [Crossref] [PubMed]
  4. P. Zhang, L. Sun, H. Yu, P. Zeng, L. Qi, and Y. Xin, “An Image Auxiliary Method for Quantitative Analysis of Laser-Induced Breakdown Spectroscopy,” Anal. Chem. 90(7), 4686–4694 (2018).
    [Crossref] [PubMed]
  5. M. Sweetapple, S. Tassios, and D. Body, “In situ analysis and mapping of lithium in Li-bearing pegmatite minerals By Laser-Induced Breakdown Spectroscopy (LIBS),” in PEG2015 poster, pp.105–106.
  6. G. S. Senesi, B. Campanella, E. Grifoni, S. Legnaioli, G. Lorenzetti, S. Pagnotta, F. Poggialini, V. Palleschi, and O. De Pascale, “Elemental and mineralogical imaging of a weathered limestone rock by double-pulse micro-Laser-Induced Breakdown Spectroscopy,” Spectrochim. Acta B At. Spectrosc. 143, 91–97 (2018).
    [Crossref]
  7. W. T. Li, Y. N. Zhu, X. Li, Z. Q. Hao, L. B. Guo, X. Y. Li, X. Y. Zeng, and Y. F. Lu, “In situ classification of rocks using stand-off laser-induced breakdown spectroscopy with a compact spectrometer,” J. Anal. At. Spectrom. 33(3), 461–467 (2018).
    [Crossref]
  8. T. Karpate, S. K. M. Muhammed, R. Nayak, V. K. Unnikrishnan, and C. Santhosh, “LIBS: a potential tool for industrial/agricultural waste water analysis,” Proc. SPIE 9893, 989317 (2016).
    [Crossref]
  9. J. Kang, R. Li, Y. Wang, Y. Chen, and Y. Yang, “Ultrasensitive detection of trace amounts of lead in water by LIBS-LIF using a wood-slice substrate as a water absorber,” J. Anal. At. Spectrom. 32(11), 2292–2299 (2017).
    [Crossref]
  10. J. L. Gottfried, “Discrimination of biological and chemical threat simulants in residue mixtures on multiple substrates,” Anal. Bioanal. Chem. 400(10), 3289–3301 (2011).
    [Crossref] [PubMed]
  11. G. Ji, P. Ye, Y. Shi, L. Yuan, X. Chen, M. Yuan, D. Zhu, X. Chen, X. Hu, and J. Jiang, “Laser-Induced Breakdown Spectroscopy for Rapid Discrimination of Heavy-Metal-Contaminated Seafood Tegillarca granosa,” Sensors (Basel) 17(11), 2655 (2017).
    [Crossref] [PubMed]
  12. C. Zhang, T. Shen, F. Liu, and Y. He, “Identification of Coffee Varieties Using Laser-Induced Breakdown Spectroscopy and Chemometrics,” Sensors (Basel) 18(2), 95 (2017).
    [Crossref] [PubMed]
  13. H. Y. Kong, L. X. Sun, J. T. Hu, Y. Xin, and Z. B. Cong, “Quantitative Analysis of Steels Using PLS with Three Data Reduction Methods Based on LIBS,” Adv. Mat. Res. 997, 578–582 (2014).
  14. N. Labbé, I. M. Swamidoss, N. André, M. Z. Martin, T. M. Young, and T. G. Rials, “Extraction of information from laser-induced breakdown spectroscopy spectral data by multivariate analysis,” Appl. Opt. 47(31), G158–G165 (2008).
    [Crossref] [PubMed]
  15. P. Yang, R. Zhou, W. Zang, S. S. Tang, Z. Q. Hao, X. Y. Li, Y. F. Lu, and X. Y. Zeng, “Laser-induced breakdown spectroscopy assisted chemometric methods for rice geographic origin classification,” Appl. Opt. 57(28), 8297–8302 (2018).
  16. P. Yang, Y. N. Zhu, X. Y. Yang, J. M. Li, S. S. Tang, Z. Q. Hao, L. B. Guo, X. Y. Li, X. Y. Zeng, and Y. F. Lu, “Evaluation of sample preparation methods for rice geographic origin classification using laser-induced breakdown spectroscopy,” J. Cereal Sci. 80, 111–118 (2018).
    [Crossref]
  17. S. Moncayo, S. Manzoor, J. D. Rosales, J. Anzano, and J. O. Caceres, “Qualitative and quantitative analysis of milk for the detection of adulteration by Laser Induced Breakdown Spectroscopy (LIBS),” Food Chem. 232, 322–328 (2017).
    [Crossref] [PubMed]
  18. P. Yang, R. Zhou, W. Zhang, R. Yi, S. Tang, L. Guo, Z. Hao, X. Li, Y. Lu, and X. Zeng, “High-sensitivity determination of cadmium and lead in rice using laser-induced breakdown spectroscopy,” Food Chem. 272, 323–328 (2019).
    [Crossref]
  19. H. Li, Y. E. Wang, Q. Liu, and D. H. Xu, “Varieties discrimination of rice seed based on laser induced breakdown spectroscopy of subsection combination,” Laser Journal 38, 8–12 (2017).
  20. Z. Q. Ke, Y. E. Wang, H. Fan, Q. Li, Liu, and J. H. Lin,”Identification of Rice Seed Varieties Based on LIBS,” Laser Journal 37, 56–60 (2016).
  21. S. J. M. Rad, F. A. Tab, and K. Mollazade, “Application of imperialist competitive algorithm for feature selection a case study on bulk rice classification,” Int. J. Comput. Appl. 40(1), 41–48 (2012).
  22. N. Dalal and B. Triggs, “Histograms of oriented gradients for human detection,” IEEE Computer Society Conference on Computer Vision and Pattern Recognition (IEEE, 2005), pp. 886–893.
  23. N. Dalal, B. Triggs, and C. Schmid, “Human Detection Using Oriented Histograms of Flow and Appearance,” in Computer Vision – ECCV 2006 (Springer Berlin Heidelberg, 2006), 428–441.
  24. S. A. M. Al-Sumaidaee, M. A. M. Abdullah, R. R. O. Al-Nima, S. S. Dlay, and J. A. Chambers, “Multi-gradient features and elongated quinary pattern encoding for image-based facial expression recognition,” Pattern Recognit. 71, 249–263 (2017).
    [Crossref]
  25. C. Cai, Y. Wang, Z. Cao, Y. Zhang, T. Lu, and D. Wang, “HOG pedestrian detection based on edge symmetry and trilinear interpolation,” 7 (2018).
  26. R. Kadota, H. Sugano, M. Hiromoto, H. Ochi, R. Miyamoto, and Y. Nakamura, “Hardware Architecture for HOG Feature Extraction,” in 2009 Fifth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, 2009), 1330–1333.
  27. Y. Wang, J. Du, X. Cheng, Z. Liu, and K. Lin, “Degradation and encryption for outsourced PNG images in cloud storage,” International Journal of Grid and Utility Computing 7(1), 22–28 (2016).
    [Crossref]
  28. A. Sophian and D. Aini, “Fingertip Detection Using Histogram of Gradients and Support Vector Machine,” Indonesian Journal of Electrical Engineering and Computer Science 8, 482–486 (2017).
  29. C. W. Hsu and C. J. Lin, “A comparison of methods for multiclass support vector machines,” IEEE Trans. Neural Netw. 13(2), 415–425 (2002).
    [Crossref] [PubMed]
  30. C. W. Hsu and C. J. Lin, “A pratical guide for support vector matchine,” 1–16 (2003).
  31. H. T. Lin and C. J. Lin, “A Study on Sigmoid Kernels for SVM and the Training of non-PSD Kernels by SMO-type Methods,” Neural Comput. 3, 1–32 (2003).
  32. M. Zhang, “Eeg feature extraction based on non-negative matrix factorization,” (Yanshan University 2014).
  33. E. Negre, V. Motto-Ros, F. Pelascini, and J. Yu, “Classification of plastic materials by imaging laser-induced ablation plumes,” Spectrochim. Acta B At. Spectrosc. 122, 132–141 (2016).
    [Crossref]

2019 (1)

P. Yang, R. Zhou, W. Zhang, R. Yi, S. Tang, L. Guo, Z. Hao, X. Li, Y. Lu, and X. Zeng, “High-sensitivity determination of cadmium and lead in rice using laser-induced breakdown spectroscopy,” Food Chem. 272, 323–328 (2019).
[Crossref]

2018 (6)

P. Yang, Y. N. Zhu, X. Y. Yang, J. M. Li, S. S. Tang, Z. Q. Hao, L. B. Guo, X. Y. Li, X. Y. Zeng, and Y. F. Lu, “Evaluation of sample preparation methods for rice geographic origin classification using laser-induced breakdown spectroscopy,” J. Cereal Sci. 80, 111–118 (2018).
[Crossref]

P. Zhang, L. Sun, H. Yu, P. Zeng, L. Qi, and Y. Xin, “An Image Auxiliary Method for Quantitative Analysis of Laser-Induced Breakdown Spectroscopy,” Anal. Chem. 90(7), 4686–4694 (2018).
[Crossref] [PubMed]

G. S. Senesi, B. Campanella, E. Grifoni, S. Legnaioli, G. Lorenzetti, S. Pagnotta, F. Poggialini, V. Palleschi, and O. De Pascale, “Elemental and mineralogical imaging of a weathered limestone rock by double-pulse micro-Laser-Induced Breakdown Spectroscopy,” Spectrochim. Acta B At. Spectrosc. 143, 91–97 (2018).
[Crossref]

W. T. Li, Y. N. Zhu, X. Li, Z. Q. Hao, L. B. Guo, X. Y. Li, X. Y. Zeng, and Y. F. Lu, “In situ classification of rocks using stand-off laser-induced breakdown spectroscopy with a compact spectrometer,” J. Anal. At. Spectrom. 33(3), 461–467 (2018).
[Crossref]

R. Yi, X. Yang, R. Zhou, J. Li, H. Yu, Z. Hao, L. Guo, X. Li, Y. Lu, and X. Zeng, “Determination of Trace Available Heavy Metals in Soil Using Laser-Induced Breakdown Spectroscopy Assisted with Phase Transformation Method,” Anal. Chem. 90(11), 7080–7085 (2018).
[Crossref] [PubMed]

P. Yang, R. Zhou, W. Zang, S. S. Tang, Z. Q. Hao, X. Y. Li, Y. F. Lu, and X. Y. Zeng, “Laser-induced breakdown spectroscopy assisted chemometric methods for rice geographic origin classification,” Appl. Opt. 57(28), 8297–8302 (2018).

2017 (7)

A. Sophian and D. Aini, “Fingertip Detection Using Histogram of Gradients and Support Vector Machine,” Indonesian Journal of Electrical Engineering and Computer Science 8, 482–486 (2017).

J. Kang, R. Li, Y. Wang, Y. Chen, and Y. Yang, “Ultrasensitive detection of trace amounts of lead in water by LIBS-LIF using a wood-slice substrate as a water absorber,” J. Anal. At. Spectrom. 32(11), 2292–2299 (2017).
[Crossref]

G. Ji, P. Ye, Y. Shi, L. Yuan, X. Chen, M. Yuan, D. Zhu, X. Chen, X. Hu, and J. Jiang, “Laser-Induced Breakdown Spectroscopy for Rapid Discrimination of Heavy-Metal-Contaminated Seafood Tegillarca granosa,” Sensors (Basel) 17(11), 2655 (2017).
[Crossref] [PubMed]

C. Zhang, T. Shen, F. Liu, and Y. He, “Identification of Coffee Varieties Using Laser-Induced Breakdown Spectroscopy and Chemometrics,” Sensors (Basel) 18(2), 95 (2017).
[Crossref] [PubMed]

S. Moncayo, S. Manzoor, J. D. Rosales, J. Anzano, and J. O. Caceres, “Qualitative and quantitative analysis of milk for the detection of adulteration by Laser Induced Breakdown Spectroscopy (LIBS),” Food Chem. 232, 322–328 (2017).
[Crossref] [PubMed]

S. A. M. Al-Sumaidaee, M. A. M. Abdullah, R. R. O. Al-Nima, S. S. Dlay, and J. A. Chambers, “Multi-gradient features and elongated quinary pattern encoding for image-based facial expression recognition,” Pattern Recognit. 71, 249–263 (2017).
[Crossref]

H. Li, Y. E. Wang, Q. Liu, and D. H. Xu, “Varieties discrimination of rice seed based on laser induced breakdown spectroscopy of subsection combination,” Laser Journal 38, 8–12 (2017).

2016 (5)

Z. Q. Ke, Y. E. Wang, H. Fan, Q. Li, Liu, and J. H. Lin,”Identification of Rice Seed Varieties Based on LIBS,” Laser Journal 37, 56–60 (2016).

Y. Wang, J. Du, X. Cheng, Z. Liu, and K. Lin, “Degradation and encryption for outsourced PNG images in cloud storage,” International Journal of Grid and Utility Computing 7(1), 22–28 (2016).
[Crossref]

T. Karpate, S. K. M. Muhammed, R. Nayak, V. K. Unnikrishnan, and C. Santhosh, “LIBS: a potential tool for industrial/agricultural waste water analysis,” Proc. SPIE 9893, 989317 (2016).
[Crossref]

E. Negre, V. Motto-Ros, F. Pelascini, and J. Yu, “Classification of plastic materials by imaging laser-induced ablation plumes,” Spectrochim. Acta B At. Spectrosc. 122, 132–141 (2016).
[Crossref]

C. Li, Z. Hao, Z. Zou, R. Zhou, J. Li, L. Guo, X. Li, Y. Lu, and X. Zeng, “Determinations of trace boron in superalloys and steels using laser-induced breakdown spectroscopy assisted with laser-induced fluorescence,” Opt. Express 24(8), 7850–7857 (2016).
[Crossref] [PubMed]

2014 (1)

H. Y. Kong, L. X. Sun, J. T. Hu, Y. Xin, and Z. B. Cong, “Quantitative Analysis of Steels Using PLS with Three Data Reduction Methods Based on LIBS,” Adv. Mat. Res. 997, 578–582 (2014).

2012 (1)

S. J. M. Rad, F. A. Tab, and K. Mollazade, “Application of imperialist competitive algorithm for feature selection a case study on bulk rice classification,” Int. J. Comput. Appl. 40(1), 41–48 (2012).

2011 (1)

J. L. Gottfried, “Discrimination of biological and chemical threat simulants in residue mixtures on multiple substrates,” Anal. Bioanal. Chem. 400(10), 3289–3301 (2011).
[Crossref] [PubMed]

2008 (2)

N. Labbé, I. M. Swamidoss, N. André, M. Z. Martin, T. M. Young, and T. G. Rials, “Extraction of information from laser-induced breakdown spectroscopy spectral data by multivariate analysis,” Appl. Opt. 47(31), G158–G165 (2008).
[Crossref] [PubMed]

Z. Chen, H. Li, M. Liu, and R. Li, “Fast and sensitive trace metal analysis in aqueous solutions by laser-induced breakdown spectroscopy using wood slice substrates,” Spectrochim. Acta B At. Spectrosc. 63(1), 64–68 (2008).
[Crossref]

2003 (1)

H. T. Lin and C. J. Lin, “A Study on Sigmoid Kernels for SVM and the Training of non-PSD Kernels by SMO-type Methods,” Neural Comput. 3, 1–32 (2003).

2002 (1)

C. W. Hsu and C. J. Lin, “A comparison of methods for multiclass support vector machines,” IEEE Trans. Neural Netw. 13(2), 415–425 (2002).
[Crossref] [PubMed]

Abdullah, M. A. M.

S. A. M. Al-Sumaidaee, M. A. M. Abdullah, R. R. O. Al-Nima, S. S. Dlay, and J. A. Chambers, “Multi-gradient features and elongated quinary pattern encoding for image-based facial expression recognition,” Pattern Recognit. 71, 249–263 (2017).
[Crossref]

Aini, D.

A. Sophian and D. Aini, “Fingertip Detection Using Histogram of Gradients and Support Vector Machine,” Indonesian Journal of Electrical Engineering and Computer Science 8, 482–486 (2017).

Al-Nima, R. R. O.

S. A. M. Al-Sumaidaee, M. A. M. Abdullah, R. R. O. Al-Nima, S. S. Dlay, and J. A. Chambers, “Multi-gradient features and elongated quinary pattern encoding for image-based facial expression recognition,” Pattern Recognit. 71, 249–263 (2017).
[Crossref]

Al-Sumaidaee, S. A. M.

S. A. M. Al-Sumaidaee, M. A. M. Abdullah, R. R. O. Al-Nima, S. S. Dlay, and J. A. Chambers, “Multi-gradient features and elongated quinary pattern encoding for image-based facial expression recognition,” Pattern Recognit. 71, 249–263 (2017).
[Crossref]

André, N.

Anzano, J.

S. Moncayo, S. Manzoor, J. D. Rosales, J. Anzano, and J. O. Caceres, “Qualitative and quantitative analysis of milk for the detection of adulteration by Laser Induced Breakdown Spectroscopy (LIBS),” Food Chem. 232, 322–328 (2017).
[Crossref] [PubMed]

Caceres, J. O.

S. Moncayo, S. Manzoor, J. D. Rosales, J. Anzano, and J. O. Caceres, “Qualitative and quantitative analysis of milk for the detection of adulteration by Laser Induced Breakdown Spectroscopy (LIBS),” Food Chem. 232, 322–328 (2017).
[Crossref] [PubMed]

Cai, C.

C. Cai, Y. Wang, Z. Cao, Y. Zhang, T. Lu, and D. Wang, “HOG pedestrian detection based on edge symmetry and trilinear interpolation,” 7 (2018).

Campanella, B.

G. S. Senesi, B. Campanella, E. Grifoni, S. Legnaioli, G. Lorenzetti, S. Pagnotta, F. Poggialini, V. Palleschi, and O. De Pascale, “Elemental and mineralogical imaging of a weathered limestone rock by double-pulse micro-Laser-Induced Breakdown Spectroscopy,” Spectrochim. Acta B At. Spectrosc. 143, 91–97 (2018).
[Crossref]

Cao, Z.

C. Cai, Y. Wang, Z. Cao, Y. Zhang, T. Lu, and D. Wang, “HOG pedestrian detection based on edge symmetry and trilinear interpolation,” 7 (2018).

Chambers, J. A.

S. A. M. Al-Sumaidaee, M. A. M. Abdullah, R. R. O. Al-Nima, S. S. Dlay, and J. A. Chambers, “Multi-gradient features and elongated quinary pattern encoding for image-based facial expression recognition,” Pattern Recognit. 71, 249–263 (2017).
[Crossref]

Chen, X.

G. Ji, P. Ye, Y. Shi, L. Yuan, X. Chen, M. Yuan, D. Zhu, X. Chen, X. Hu, and J. Jiang, “Laser-Induced Breakdown Spectroscopy for Rapid Discrimination of Heavy-Metal-Contaminated Seafood Tegillarca granosa,” Sensors (Basel) 17(11), 2655 (2017).
[Crossref] [PubMed]

G. Ji, P. Ye, Y. Shi, L. Yuan, X. Chen, M. Yuan, D. Zhu, X. Chen, X. Hu, and J. Jiang, “Laser-Induced Breakdown Spectroscopy for Rapid Discrimination of Heavy-Metal-Contaminated Seafood Tegillarca granosa,” Sensors (Basel) 17(11), 2655 (2017).
[Crossref] [PubMed]

Chen, Y.

J. Kang, R. Li, Y. Wang, Y. Chen, and Y. Yang, “Ultrasensitive detection of trace amounts of lead in water by LIBS-LIF using a wood-slice substrate as a water absorber,” J. Anal. At. Spectrom. 32(11), 2292–2299 (2017).
[Crossref]

Chen, Z.

Z. Chen, H. Li, M. Liu, and R. Li, “Fast and sensitive trace metal analysis in aqueous solutions by laser-induced breakdown spectroscopy using wood slice substrates,” Spectrochim. Acta B At. Spectrosc. 63(1), 64–68 (2008).
[Crossref]

Cheng, X.

Y. Wang, J. Du, X. Cheng, Z. Liu, and K. Lin, “Degradation and encryption for outsourced PNG images in cloud storage,” International Journal of Grid and Utility Computing 7(1), 22–28 (2016).
[Crossref]

Cong, Z. B.

H. Y. Kong, L. X. Sun, J. T. Hu, Y. Xin, and Z. B. Cong, “Quantitative Analysis of Steels Using PLS with Three Data Reduction Methods Based on LIBS,” Adv. Mat. Res. 997, 578–582 (2014).

Dalal, N.

N. Dalal and B. Triggs, “Histograms of oriented gradients for human detection,” IEEE Computer Society Conference on Computer Vision and Pattern Recognition (IEEE, 2005), pp. 886–893.

De Pascale, O.

G. S. Senesi, B. Campanella, E. Grifoni, S. Legnaioli, G. Lorenzetti, S. Pagnotta, F. Poggialini, V. Palleschi, and O. De Pascale, “Elemental and mineralogical imaging of a weathered limestone rock by double-pulse micro-Laser-Induced Breakdown Spectroscopy,” Spectrochim. Acta B At. Spectrosc. 143, 91–97 (2018).
[Crossref]

Dlay, S. S.

S. A. M. Al-Sumaidaee, M. A. M. Abdullah, R. R. O. Al-Nima, S. S. Dlay, and J. A. Chambers, “Multi-gradient features and elongated quinary pattern encoding for image-based facial expression recognition,” Pattern Recognit. 71, 249–263 (2017).
[Crossref]

Du, J.

Y. Wang, J. Du, X. Cheng, Z. Liu, and K. Lin, “Degradation and encryption for outsourced PNG images in cloud storage,” International Journal of Grid and Utility Computing 7(1), 22–28 (2016).
[Crossref]

Fan, H.

Z. Q. Ke, Y. E. Wang, H. Fan, Q. Li, Liu, and J. H. Lin,”Identification of Rice Seed Varieties Based on LIBS,” Laser Journal 37, 56–60 (2016).

Gottfried, J. L.

J. L. Gottfried, “Discrimination of biological and chemical threat simulants in residue mixtures on multiple substrates,” Anal. Bioanal. Chem. 400(10), 3289–3301 (2011).
[Crossref] [PubMed]

Grifoni, E.

G. S. Senesi, B. Campanella, E. Grifoni, S. Legnaioli, G. Lorenzetti, S. Pagnotta, F. Poggialini, V. Palleschi, and O. De Pascale, “Elemental and mineralogical imaging of a weathered limestone rock by double-pulse micro-Laser-Induced Breakdown Spectroscopy,” Spectrochim. Acta B At. Spectrosc. 143, 91–97 (2018).
[Crossref]

Guo, L.

P. Yang, R. Zhou, W. Zhang, R. Yi, S. Tang, L. Guo, Z. Hao, X. Li, Y. Lu, and X. Zeng, “High-sensitivity determination of cadmium and lead in rice using laser-induced breakdown spectroscopy,” Food Chem. 272, 323–328 (2019).
[Crossref]

R. Yi, X. Yang, R. Zhou, J. Li, H. Yu, Z. Hao, L. Guo, X. Li, Y. Lu, and X. Zeng, “Determination of Trace Available Heavy Metals in Soil Using Laser-Induced Breakdown Spectroscopy Assisted with Phase Transformation Method,” Anal. Chem. 90(11), 7080–7085 (2018).
[Crossref] [PubMed]

C. Li, Z. Hao, Z. Zou, R. Zhou, J. Li, L. Guo, X. Li, Y. Lu, and X. Zeng, “Determinations of trace boron in superalloys and steels using laser-induced breakdown spectroscopy assisted with laser-induced fluorescence,” Opt. Express 24(8), 7850–7857 (2016).
[Crossref] [PubMed]

Guo, L. B.

P. Yang, Y. N. Zhu, X. Y. Yang, J. M. Li, S. S. Tang, Z. Q. Hao, L. B. Guo, X. Y. Li, X. Y. Zeng, and Y. F. Lu, “Evaluation of sample preparation methods for rice geographic origin classification using laser-induced breakdown spectroscopy,” J. Cereal Sci. 80, 111–118 (2018).
[Crossref]

W. T. Li, Y. N. Zhu, X. Li, Z. Q. Hao, L. B. Guo, X. Y. Li, X. Y. Zeng, and Y. F. Lu, “In situ classification of rocks using stand-off laser-induced breakdown spectroscopy with a compact spectrometer,” J. Anal. At. Spectrom. 33(3), 461–467 (2018).
[Crossref]

Hao, Z.

P. Yang, R. Zhou, W. Zhang, R. Yi, S. Tang, L. Guo, Z. Hao, X. Li, Y. Lu, and X. Zeng, “High-sensitivity determination of cadmium and lead in rice using laser-induced breakdown spectroscopy,” Food Chem. 272, 323–328 (2019).
[Crossref]

R. Yi, X. Yang, R. Zhou, J. Li, H. Yu, Z. Hao, L. Guo, X. Li, Y. Lu, and X. Zeng, “Determination of Trace Available Heavy Metals in Soil Using Laser-Induced Breakdown Spectroscopy Assisted with Phase Transformation Method,” Anal. Chem. 90(11), 7080–7085 (2018).
[Crossref] [PubMed]

C. Li, Z. Hao, Z. Zou, R. Zhou, J. Li, L. Guo, X. Li, Y. Lu, and X. Zeng, “Determinations of trace boron in superalloys and steels using laser-induced breakdown spectroscopy assisted with laser-induced fluorescence,” Opt. Express 24(8), 7850–7857 (2016).
[Crossref] [PubMed]

Hao, Z. Q.

P. Yang, Y. N. Zhu, X. Y. Yang, J. M. Li, S. S. Tang, Z. Q. Hao, L. B. Guo, X. Y. Li, X. Y. Zeng, and Y. F. Lu, “Evaluation of sample preparation methods for rice geographic origin classification using laser-induced breakdown spectroscopy,” J. Cereal Sci. 80, 111–118 (2018).
[Crossref]

W. T. Li, Y. N. Zhu, X. Li, Z. Q. Hao, L. B. Guo, X. Y. Li, X. Y. Zeng, and Y. F. Lu, “In situ classification of rocks using stand-off laser-induced breakdown spectroscopy with a compact spectrometer,” J. Anal. At. Spectrom. 33(3), 461–467 (2018).
[Crossref]

P. Yang, R. Zhou, W. Zang, S. S. Tang, Z. Q. Hao, X. Y. Li, Y. F. Lu, and X. Y. Zeng, “Laser-induced breakdown spectroscopy assisted chemometric methods for rice geographic origin classification,” Appl. Opt. 57(28), 8297–8302 (2018).

He, Y.

C. Zhang, T. Shen, F. Liu, and Y. He, “Identification of Coffee Varieties Using Laser-Induced Breakdown Spectroscopy and Chemometrics,” Sensors (Basel) 18(2), 95 (2017).
[Crossref] [PubMed]

Hiromoto, M.

R. Kadota, H. Sugano, M. Hiromoto, H. Ochi, R. Miyamoto, and Y. Nakamura, “Hardware Architecture for HOG Feature Extraction,” in 2009 Fifth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, 2009), 1330–1333.

Hsu, C. W.

C. W. Hsu and C. J. Lin, “A comparison of methods for multiclass support vector machines,” IEEE Trans. Neural Netw. 13(2), 415–425 (2002).
[Crossref] [PubMed]

C. W. Hsu and C. J. Lin, “A pratical guide for support vector matchine,” 1–16 (2003).

Hu, J. T.

H. Y. Kong, L. X. Sun, J. T. Hu, Y. Xin, and Z. B. Cong, “Quantitative Analysis of Steels Using PLS with Three Data Reduction Methods Based on LIBS,” Adv. Mat. Res. 997, 578–582 (2014).

Hu, X.

G. Ji, P. Ye, Y. Shi, L. Yuan, X. Chen, M. Yuan, D. Zhu, X. Chen, X. Hu, and J. Jiang, “Laser-Induced Breakdown Spectroscopy for Rapid Discrimination of Heavy-Metal-Contaminated Seafood Tegillarca granosa,” Sensors (Basel) 17(11), 2655 (2017).
[Crossref] [PubMed]

Ji, G.

G. Ji, P. Ye, Y. Shi, L. Yuan, X. Chen, M. Yuan, D. Zhu, X. Chen, X. Hu, and J. Jiang, “Laser-Induced Breakdown Spectroscopy for Rapid Discrimination of Heavy-Metal-Contaminated Seafood Tegillarca granosa,” Sensors (Basel) 17(11), 2655 (2017).
[Crossref] [PubMed]

Jiang, J.

G. Ji, P. Ye, Y. Shi, L. Yuan, X. Chen, M. Yuan, D. Zhu, X. Chen, X. Hu, and J. Jiang, “Laser-Induced Breakdown Spectroscopy for Rapid Discrimination of Heavy-Metal-Contaminated Seafood Tegillarca granosa,” Sensors (Basel) 17(11), 2655 (2017).
[Crossref] [PubMed]

Kadota, R.

R. Kadota, H. Sugano, M. Hiromoto, H. Ochi, R. Miyamoto, and Y. Nakamura, “Hardware Architecture for HOG Feature Extraction,” in 2009 Fifth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, 2009), 1330–1333.

Kang, J.

J. Kang, R. Li, Y. Wang, Y. Chen, and Y. Yang, “Ultrasensitive detection of trace amounts of lead in water by LIBS-LIF using a wood-slice substrate as a water absorber,” J. Anal. At. Spectrom. 32(11), 2292–2299 (2017).
[Crossref]

Karpate, T.

T. Karpate, S. K. M. Muhammed, R. Nayak, V. K. Unnikrishnan, and C. Santhosh, “LIBS: a potential tool for industrial/agricultural waste water analysis,” Proc. SPIE 9893, 989317 (2016).
[Crossref]

Ke, Z. Q.

Z. Q. Ke, Y. E. Wang, H. Fan, Q. Li, Liu, and J. H. Lin,”Identification of Rice Seed Varieties Based on LIBS,” Laser Journal 37, 56–60 (2016).

Kong, H. Y.

H. Y. Kong, L. X. Sun, J. T. Hu, Y. Xin, and Z. B. Cong, “Quantitative Analysis of Steels Using PLS with Three Data Reduction Methods Based on LIBS,” Adv. Mat. Res. 997, 578–582 (2014).

Labbé, N.

Legnaioli, S.

G. S. Senesi, B. Campanella, E. Grifoni, S. Legnaioli, G. Lorenzetti, S. Pagnotta, F. Poggialini, V. Palleschi, and O. De Pascale, “Elemental and mineralogical imaging of a weathered limestone rock by double-pulse micro-Laser-Induced Breakdown Spectroscopy,” Spectrochim. Acta B At. Spectrosc. 143, 91–97 (2018).
[Crossref]

Li, C.

Li, H.

H. Li, Y. E. Wang, Q. Liu, and D. H. Xu, “Varieties discrimination of rice seed based on laser induced breakdown spectroscopy of subsection combination,” Laser Journal 38, 8–12 (2017).

Z. Chen, H. Li, M. Liu, and R. Li, “Fast and sensitive trace metal analysis in aqueous solutions by laser-induced breakdown spectroscopy using wood slice substrates,” Spectrochim. Acta B At. Spectrosc. 63(1), 64–68 (2008).
[Crossref]

Li, J.

R. Yi, X. Yang, R. Zhou, J. Li, H. Yu, Z. Hao, L. Guo, X. Li, Y. Lu, and X. Zeng, “Determination of Trace Available Heavy Metals in Soil Using Laser-Induced Breakdown Spectroscopy Assisted with Phase Transformation Method,” Anal. Chem. 90(11), 7080–7085 (2018).
[Crossref] [PubMed]

C. Li, Z. Hao, Z. Zou, R. Zhou, J. Li, L. Guo, X. Li, Y. Lu, and X. Zeng, “Determinations of trace boron in superalloys and steels using laser-induced breakdown spectroscopy assisted with laser-induced fluorescence,” Opt. Express 24(8), 7850–7857 (2016).
[Crossref] [PubMed]

Li, J. M.

P. Yang, Y. N. Zhu, X. Y. Yang, J. M. Li, S. S. Tang, Z. Q. Hao, L. B. Guo, X. Y. Li, X. Y. Zeng, and Y. F. Lu, “Evaluation of sample preparation methods for rice geographic origin classification using laser-induced breakdown spectroscopy,” J. Cereal Sci. 80, 111–118 (2018).
[Crossref]

Li, Q.

Z. Q. Ke, Y. E. Wang, H. Fan, Q. Li, Liu, and J. H. Lin,”Identification of Rice Seed Varieties Based on LIBS,” Laser Journal 37, 56–60 (2016).

Li, R.

J. Kang, R. Li, Y. Wang, Y. Chen, and Y. Yang, “Ultrasensitive detection of trace amounts of lead in water by LIBS-LIF using a wood-slice substrate as a water absorber,” J. Anal. At. Spectrom. 32(11), 2292–2299 (2017).
[Crossref]

Z. Chen, H. Li, M. Liu, and R. Li, “Fast and sensitive trace metal analysis in aqueous solutions by laser-induced breakdown spectroscopy using wood slice substrates,” Spectrochim. Acta B At. Spectrosc. 63(1), 64–68 (2008).
[Crossref]

Li, W. T.

W. T. Li, Y. N. Zhu, X. Li, Z. Q. Hao, L. B. Guo, X. Y. Li, X. Y. Zeng, and Y. F. Lu, “In situ classification of rocks using stand-off laser-induced breakdown spectroscopy with a compact spectrometer,” J. Anal. At. Spectrom. 33(3), 461–467 (2018).
[Crossref]

Li, X.

P. Yang, R. Zhou, W. Zhang, R. Yi, S. Tang, L. Guo, Z. Hao, X. Li, Y. Lu, and X. Zeng, “High-sensitivity determination of cadmium and lead in rice using laser-induced breakdown spectroscopy,” Food Chem. 272, 323–328 (2019).
[Crossref]

W. T. Li, Y. N. Zhu, X. Li, Z. Q. Hao, L. B. Guo, X. Y. Li, X. Y. Zeng, and Y. F. Lu, “In situ classification of rocks using stand-off laser-induced breakdown spectroscopy with a compact spectrometer,” J. Anal. At. Spectrom. 33(3), 461–467 (2018).
[Crossref]

R. Yi, X. Yang, R. Zhou, J. Li, H. Yu, Z. Hao, L. Guo, X. Li, Y. Lu, and X. Zeng, “Determination of Trace Available Heavy Metals in Soil Using Laser-Induced Breakdown Spectroscopy Assisted with Phase Transformation Method,” Anal. Chem. 90(11), 7080–7085 (2018).
[Crossref] [PubMed]

C. Li, Z. Hao, Z. Zou, R. Zhou, J. Li, L. Guo, X. Li, Y. Lu, and X. Zeng, “Determinations of trace boron in superalloys and steels using laser-induced breakdown spectroscopy assisted with laser-induced fluorescence,” Opt. Express 24(8), 7850–7857 (2016).
[Crossref] [PubMed]

Li, X. Y.

P. Yang, R. Zhou, W. Zang, S. S. Tang, Z. Q. Hao, X. Y. Li, Y. F. Lu, and X. Y. Zeng, “Laser-induced breakdown spectroscopy assisted chemometric methods for rice geographic origin classification,” Appl. Opt. 57(28), 8297–8302 (2018).

W. T. Li, Y. N. Zhu, X. Li, Z. Q. Hao, L. B. Guo, X. Y. Li, X. Y. Zeng, and Y. F. Lu, “In situ classification of rocks using stand-off laser-induced breakdown spectroscopy with a compact spectrometer,” J. Anal. At. Spectrom. 33(3), 461–467 (2018).
[Crossref]

P. Yang, Y. N. Zhu, X. Y. Yang, J. M. Li, S. S. Tang, Z. Q. Hao, L. B. Guo, X. Y. Li, X. Y. Zeng, and Y. F. Lu, “Evaluation of sample preparation methods for rice geographic origin classification using laser-induced breakdown spectroscopy,” J. Cereal Sci. 80, 111–118 (2018).
[Crossref]

Lin, C. J.

H. T. Lin and C. J. Lin, “A Study on Sigmoid Kernels for SVM and the Training of non-PSD Kernels by SMO-type Methods,” Neural Comput. 3, 1–32 (2003).

C. W. Hsu and C. J. Lin, “A comparison of methods for multiclass support vector machines,” IEEE Trans. Neural Netw. 13(2), 415–425 (2002).
[Crossref] [PubMed]

C. W. Hsu and C. J. Lin, “A pratical guide for support vector matchine,” 1–16 (2003).

Lin, H. T.

H. T. Lin and C. J. Lin, “A Study on Sigmoid Kernels for SVM and the Training of non-PSD Kernels by SMO-type Methods,” Neural Comput. 3, 1–32 (2003).

Lin, J. H.

Z. Q. Ke, Y. E. Wang, H. Fan, Q. Li, Liu, and J. H. Lin,”Identification of Rice Seed Varieties Based on LIBS,” Laser Journal 37, 56–60 (2016).

Lin, K.

Y. Wang, J. Du, X. Cheng, Z. Liu, and K. Lin, “Degradation and encryption for outsourced PNG images in cloud storage,” International Journal of Grid and Utility Computing 7(1), 22–28 (2016).
[Crossref]

Liu,

Z. Q. Ke, Y. E. Wang, H. Fan, Q. Li, Liu, and J. H. Lin,”Identification of Rice Seed Varieties Based on LIBS,” Laser Journal 37, 56–60 (2016).

Liu, F.

C. Zhang, T. Shen, F. Liu, and Y. He, “Identification of Coffee Varieties Using Laser-Induced Breakdown Spectroscopy and Chemometrics,” Sensors (Basel) 18(2), 95 (2017).
[Crossref] [PubMed]

Liu, M.

Z. Chen, H. Li, M. Liu, and R. Li, “Fast and sensitive trace metal analysis in aqueous solutions by laser-induced breakdown spectroscopy using wood slice substrates,” Spectrochim. Acta B At. Spectrosc. 63(1), 64–68 (2008).
[Crossref]

Liu, Q.

H. Li, Y. E. Wang, Q. Liu, and D. H. Xu, “Varieties discrimination of rice seed based on laser induced breakdown spectroscopy of subsection combination,” Laser Journal 38, 8–12 (2017).

Liu, Z.

Y. Wang, J. Du, X. Cheng, Z. Liu, and K. Lin, “Degradation and encryption for outsourced PNG images in cloud storage,” International Journal of Grid and Utility Computing 7(1), 22–28 (2016).
[Crossref]

Lorenzetti, G.

G. S. Senesi, B. Campanella, E. Grifoni, S. Legnaioli, G. Lorenzetti, S. Pagnotta, F. Poggialini, V. Palleschi, and O. De Pascale, “Elemental and mineralogical imaging of a weathered limestone rock by double-pulse micro-Laser-Induced Breakdown Spectroscopy,” Spectrochim. Acta B At. Spectrosc. 143, 91–97 (2018).
[Crossref]

Lu, T.

C. Cai, Y. Wang, Z. Cao, Y. Zhang, T. Lu, and D. Wang, “HOG pedestrian detection based on edge symmetry and trilinear interpolation,” 7 (2018).

Lu, Y.

P. Yang, R. Zhou, W. Zhang, R. Yi, S. Tang, L. Guo, Z. Hao, X. Li, Y. Lu, and X. Zeng, “High-sensitivity determination of cadmium and lead in rice using laser-induced breakdown spectroscopy,” Food Chem. 272, 323–328 (2019).
[Crossref]

R. Yi, X. Yang, R. Zhou, J. Li, H. Yu, Z. Hao, L. Guo, X. Li, Y. Lu, and X. Zeng, “Determination of Trace Available Heavy Metals in Soil Using Laser-Induced Breakdown Spectroscopy Assisted with Phase Transformation Method,” Anal. Chem. 90(11), 7080–7085 (2018).
[Crossref] [PubMed]

C. Li, Z. Hao, Z. Zou, R. Zhou, J. Li, L. Guo, X. Li, Y. Lu, and X. Zeng, “Determinations of trace boron in superalloys and steels using laser-induced breakdown spectroscopy assisted with laser-induced fluorescence,” Opt. Express 24(8), 7850–7857 (2016).
[Crossref] [PubMed]

Lu, Y. F.

P. Yang, R. Zhou, W. Zang, S. S. Tang, Z. Q. Hao, X. Y. Li, Y. F. Lu, and X. Y. Zeng, “Laser-induced breakdown spectroscopy assisted chemometric methods for rice geographic origin classification,” Appl. Opt. 57(28), 8297–8302 (2018).

P. Yang, Y. N. Zhu, X. Y. Yang, J. M. Li, S. S. Tang, Z. Q. Hao, L. B. Guo, X. Y. Li, X. Y. Zeng, and Y. F. Lu, “Evaluation of sample preparation methods for rice geographic origin classification using laser-induced breakdown spectroscopy,” J. Cereal Sci. 80, 111–118 (2018).
[Crossref]

W. T. Li, Y. N. Zhu, X. Li, Z. Q. Hao, L. B. Guo, X. Y. Li, X. Y. Zeng, and Y. F. Lu, “In situ classification of rocks using stand-off laser-induced breakdown spectroscopy with a compact spectrometer,” J. Anal. At. Spectrom. 33(3), 461–467 (2018).
[Crossref]

Manzoor, S.

S. Moncayo, S. Manzoor, J. D. Rosales, J. Anzano, and J. O. Caceres, “Qualitative and quantitative analysis of milk for the detection of adulteration by Laser Induced Breakdown Spectroscopy (LIBS),” Food Chem. 232, 322–328 (2017).
[Crossref] [PubMed]

Martin, M. Z.

Miyamoto, R.

R. Kadota, H. Sugano, M. Hiromoto, H. Ochi, R. Miyamoto, and Y. Nakamura, “Hardware Architecture for HOG Feature Extraction,” in 2009 Fifth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, 2009), 1330–1333.

Mollazade, K.

S. J. M. Rad, F. A. Tab, and K. Mollazade, “Application of imperialist competitive algorithm for feature selection a case study on bulk rice classification,” Int. J. Comput. Appl. 40(1), 41–48 (2012).

Moncayo, S.

S. Moncayo, S. Manzoor, J. D. Rosales, J. Anzano, and J. O. Caceres, “Qualitative and quantitative analysis of milk for the detection of adulteration by Laser Induced Breakdown Spectroscopy (LIBS),” Food Chem. 232, 322–328 (2017).
[Crossref] [PubMed]

Motto-Ros, V.

E. Negre, V. Motto-Ros, F. Pelascini, and J. Yu, “Classification of plastic materials by imaging laser-induced ablation plumes,” Spectrochim. Acta B At. Spectrosc. 122, 132–141 (2016).
[Crossref]

Muhammed, S. K. M.

T. Karpate, S. K. M. Muhammed, R. Nayak, V. K. Unnikrishnan, and C. Santhosh, “LIBS: a potential tool for industrial/agricultural waste water analysis,” Proc. SPIE 9893, 989317 (2016).
[Crossref]

Nakamura, Y.

R. Kadota, H. Sugano, M. Hiromoto, H. Ochi, R. Miyamoto, and Y. Nakamura, “Hardware Architecture for HOG Feature Extraction,” in 2009 Fifth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, 2009), 1330–1333.

Nayak, R.

T. Karpate, S. K. M. Muhammed, R. Nayak, V. K. Unnikrishnan, and C. Santhosh, “LIBS: a potential tool for industrial/agricultural waste water analysis,” Proc. SPIE 9893, 989317 (2016).
[Crossref]

Negre, E.

E. Negre, V. Motto-Ros, F. Pelascini, and J. Yu, “Classification of plastic materials by imaging laser-induced ablation plumes,” Spectrochim. Acta B At. Spectrosc. 122, 132–141 (2016).
[Crossref]

Ochi, H.

R. Kadota, H. Sugano, M. Hiromoto, H. Ochi, R. Miyamoto, and Y. Nakamura, “Hardware Architecture for HOG Feature Extraction,” in 2009 Fifth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, 2009), 1330–1333.

Pagnotta, S.

G. S. Senesi, B. Campanella, E. Grifoni, S. Legnaioli, G. Lorenzetti, S. Pagnotta, F. Poggialini, V. Palleschi, and O. De Pascale, “Elemental and mineralogical imaging of a weathered limestone rock by double-pulse micro-Laser-Induced Breakdown Spectroscopy,” Spectrochim. Acta B At. Spectrosc. 143, 91–97 (2018).
[Crossref]

Palleschi, V.

G. S. Senesi, B. Campanella, E. Grifoni, S. Legnaioli, G. Lorenzetti, S. Pagnotta, F. Poggialini, V. Palleschi, and O. De Pascale, “Elemental and mineralogical imaging of a weathered limestone rock by double-pulse micro-Laser-Induced Breakdown Spectroscopy,” Spectrochim. Acta B At. Spectrosc. 143, 91–97 (2018).
[Crossref]

Pelascini, F.

E. Negre, V. Motto-Ros, F. Pelascini, and J. Yu, “Classification of plastic materials by imaging laser-induced ablation plumes,” Spectrochim. Acta B At. Spectrosc. 122, 132–141 (2016).
[Crossref]

Poggialini, F.

G. S. Senesi, B. Campanella, E. Grifoni, S. Legnaioli, G. Lorenzetti, S. Pagnotta, F. Poggialini, V. Palleschi, and O. De Pascale, “Elemental and mineralogical imaging of a weathered limestone rock by double-pulse micro-Laser-Induced Breakdown Spectroscopy,” Spectrochim. Acta B At. Spectrosc. 143, 91–97 (2018).
[Crossref]

Qi, L.

P. Zhang, L. Sun, H. Yu, P. Zeng, L. Qi, and Y. Xin, “An Image Auxiliary Method for Quantitative Analysis of Laser-Induced Breakdown Spectroscopy,” Anal. Chem. 90(7), 4686–4694 (2018).
[Crossref] [PubMed]

Rad, S. J. M.

S. J. M. Rad, F. A. Tab, and K. Mollazade, “Application of imperialist competitive algorithm for feature selection a case study on bulk rice classification,” Int. J. Comput. Appl. 40(1), 41–48 (2012).

Rials, T. G.

Rosales, J. D.

S. Moncayo, S. Manzoor, J. D. Rosales, J. Anzano, and J. O. Caceres, “Qualitative and quantitative analysis of milk for the detection of adulteration by Laser Induced Breakdown Spectroscopy (LIBS),” Food Chem. 232, 322–328 (2017).
[Crossref] [PubMed]

Santhosh, C.

T. Karpate, S. K. M. Muhammed, R. Nayak, V. K. Unnikrishnan, and C. Santhosh, “LIBS: a potential tool for industrial/agricultural waste water analysis,” Proc. SPIE 9893, 989317 (2016).
[Crossref]

Senesi, G. S.

G. S. Senesi, B. Campanella, E. Grifoni, S. Legnaioli, G. Lorenzetti, S. Pagnotta, F. Poggialini, V. Palleschi, and O. De Pascale, “Elemental and mineralogical imaging of a weathered limestone rock by double-pulse micro-Laser-Induced Breakdown Spectroscopy,” Spectrochim. Acta B At. Spectrosc. 143, 91–97 (2018).
[Crossref]

Shen, T.

C. Zhang, T. Shen, F. Liu, and Y. He, “Identification of Coffee Varieties Using Laser-Induced Breakdown Spectroscopy and Chemometrics,” Sensors (Basel) 18(2), 95 (2017).
[Crossref] [PubMed]

Shi, Y.

G. Ji, P. Ye, Y. Shi, L. Yuan, X. Chen, M. Yuan, D. Zhu, X. Chen, X. Hu, and J. Jiang, “Laser-Induced Breakdown Spectroscopy for Rapid Discrimination of Heavy-Metal-Contaminated Seafood Tegillarca granosa,” Sensors (Basel) 17(11), 2655 (2017).
[Crossref] [PubMed]

Sophian, A.

A. Sophian and D. Aini, “Fingertip Detection Using Histogram of Gradients and Support Vector Machine,” Indonesian Journal of Electrical Engineering and Computer Science 8, 482–486 (2017).

Sugano, H.

R. Kadota, H. Sugano, M. Hiromoto, H. Ochi, R. Miyamoto, and Y. Nakamura, “Hardware Architecture for HOG Feature Extraction,” in 2009 Fifth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, 2009), 1330–1333.

Sun, L.

P. Zhang, L. Sun, H. Yu, P. Zeng, L. Qi, and Y. Xin, “An Image Auxiliary Method for Quantitative Analysis of Laser-Induced Breakdown Spectroscopy,” Anal. Chem. 90(7), 4686–4694 (2018).
[Crossref] [PubMed]

Sun, L. X.

H. Y. Kong, L. X. Sun, J. T. Hu, Y. Xin, and Z. B. Cong, “Quantitative Analysis of Steels Using PLS with Three Data Reduction Methods Based on LIBS,” Adv. Mat. Res. 997, 578–582 (2014).

Swamidoss, I. M.

Tab, F. A.

S. J. M. Rad, F. A. Tab, and K. Mollazade, “Application of imperialist competitive algorithm for feature selection a case study on bulk rice classification,” Int. J. Comput. Appl. 40(1), 41–48 (2012).

Tang, S.

P. Yang, R. Zhou, W. Zhang, R. Yi, S. Tang, L. Guo, Z. Hao, X. Li, Y. Lu, and X. Zeng, “High-sensitivity determination of cadmium and lead in rice using laser-induced breakdown spectroscopy,” Food Chem. 272, 323–328 (2019).
[Crossref]

Tang, S. S.

P. Yang, Y. N. Zhu, X. Y. Yang, J. M. Li, S. S. Tang, Z. Q. Hao, L. B. Guo, X. Y. Li, X. Y. Zeng, and Y. F. Lu, “Evaluation of sample preparation methods for rice geographic origin classification using laser-induced breakdown spectroscopy,” J. Cereal Sci. 80, 111–118 (2018).
[Crossref]

P. Yang, R. Zhou, W. Zang, S. S. Tang, Z. Q. Hao, X. Y. Li, Y. F. Lu, and X. Y. Zeng, “Laser-induced breakdown spectroscopy assisted chemometric methods for rice geographic origin classification,” Appl. Opt. 57(28), 8297–8302 (2018).

Triggs, B.

N. Dalal and B. Triggs, “Histograms of oriented gradients for human detection,” IEEE Computer Society Conference on Computer Vision and Pattern Recognition (IEEE, 2005), pp. 886–893.

Unnikrishnan, V. K.

T. Karpate, S. K. M. Muhammed, R. Nayak, V. K. Unnikrishnan, and C. Santhosh, “LIBS: a potential tool for industrial/agricultural waste water analysis,” Proc. SPIE 9893, 989317 (2016).
[Crossref]

Wang, D.

C. Cai, Y. Wang, Z. Cao, Y. Zhang, T. Lu, and D. Wang, “HOG pedestrian detection based on edge symmetry and trilinear interpolation,” 7 (2018).

Wang, Y.

J. Kang, R. Li, Y. Wang, Y. Chen, and Y. Yang, “Ultrasensitive detection of trace amounts of lead in water by LIBS-LIF using a wood-slice substrate as a water absorber,” J. Anal. At. Spectrom. 32(11), 2292–2299 (2017).
[Crossref]

Y. Wang, J. Du, X. Cheng, Z. Liu, and K. Lin, “Degradation and encryption for outsourced PNG images in cloud storage,” International Journal of Grid and Utility Computing 7(1), 22–28 (2016).
[Crossref]

C. Cai, Y. Wang, Z. Cao, Y. Zhang, T. Lu, and D. Wang, “HOG pedestrian detection based on edge symmetry and trilinear interpolation,” 7 (2018).

Wang, Y. E.

H. Li, Y. E. Wang, Q. Liu, and D. H. Xu, “Varieties discrimination of rice seed based on laser induced breakdown spectroscopy of subsection combination,” Laser Journal 38, 8–12 (2017).

Z. Q. Ke, Y. E. Wang, H. Fan, Q. Li, Liu, and J. H. Lin,”Identification of Rice Seed Varieties Based on LIBS,” Laser Journal 37, 56–60 (2016).

Xin, Y.

P. Zhang, L. Sun, H. Yu, P. Zeng, L. Qi, and Y. Xin, “An Image Auxiliary Method for Quantitative Analysis of Laser-Induced Breakdown Spectroscopy,” Anal. Chem. 90(7), 4686–4694 (2018).
[Crossref] [PubMed]

H. Y. Kong, L. X. Sun, J. T. Hu, Y. Xin, and Z. B. Cong, “Quantitative Analysis of Steels Using PLS with Three Data Reduction Methods Based on LIBS,” Adv. Mat. Res. 997, 578–582 (2014).

Xu, D. H.

H. Li, Y. E. Wang, Q. Liu, and D. H. Xu, “Varieties discrimination of rice seed based on laser induced breakdown spectroscopy of subsection combination,” Laser Journal 38, 8–12 (2017).

Yang, P.

P. Yang, R. Zhou, W. Zhang, R. Yi, S. Tang, L. Guo, Z. Hao, X. Li, Y. Lu, and X. Zeng, “High-sensitivity determination of cadmium and lead in rice using laser-induced breakdown spectroscopy,” Food Chem. 272, 323–328 (2019).
[Crossref]

P. Yang, Y. N. Zhu, X. Y. Yang, J. M. Li, S. S. Tang, Z. Q. Hao, L. B. Guo, X. Y. Li, X. Y. Zeng, and Y. F. Lu, “Evaluation of sample preparation methods for rice geographic origin classification using laser-induced breakdown spectroscopy,” J. Cereal Sci. 80, 111–118 (2018).
[Crossref]

P. Yang, R. Zhou, W. Zang, S. S. Tang, Z. Q. Hao, X. Y. Li, Y. F. Lu, and X. Y. Zeng, “Laser-induced breakdown spectroscopy assisted chemometric methods for rice geographic origin classification,” Appl. Opt. 57(28), 8297–8302 (2018).

Yang, X.

R. Yi, X. Yang, R. Zhou, J. Li, H. Yu, Z. Hao, L. Guo, X. Li, Y. Lu, and X. Zeng, “Determination of Trace Available Heavy Metals in Soil Using Laser-Induced Breakdown Spectroscopy Assisted with Phase Transformation Method,” Anal. Chem. 90(11), 7080–7085 (2018).
[Crossref] [PubMed]

Yang, X. Y.

P. Yang, Y. N. Zhu, X. Y. Yang, J. M. Li, S. S. Tang, Z. Q. Hao, L. B. Guo, X. Y. Li, X. Y. Zeng, and Y. F. Lu, “Evaluation of sample preparation methods for rice geographic origin classification using laser-induced breakdown spectroscopy,” J. Cereal Sci. 80, 111–118 (2018).
[Crossref]

Yang, Y.

J. Kang, R. Li, Y. Wang, Y. Chen, and Y. Yang, “Ultrasensitive detection of trace amounts of lead in water by LIBS-LIF using a wood-slice substrate as a water absorber,” J. Anal. At. Spectrom. 32(11), 2292–2299 (2017).
[Crossref]

Ye, P.

G. Ji, P. Ye, Y. Shi, L. Yuan, X. Chen, M. Yuan, D. Zhu, X. Chen, X. Hu, and J. Jiang, “Laser-Induced Breakdown Spectroscopy for Rapid Discrimination of Heavy-Metal-Contaminated Seafood Tegillarca granosa,” Sensors (Basel) 17(11), 2655 (2017).
[Crossref] [PubMed]

Yi, R.

P. Yang, R. Zhou, W. Zhang, R. Yi, S. Tang, L. Guo, Z. Hao, X. Li, Y. Lu, and X. Zeng, “High-sensitivity determination of cadmium and lead in rice using laser-induced breakdown spectroscopy,” Food Chem. 272, 323–328 (2019).
[Crossref]

R. Yi, X. Yang, R. Zhou, J. Li, H. Yu, Z. Hao, L. Guo, X. Li, Y. Lu, and X. Zeng, “Determination of Trace Available Heavy Metals in Soil Using Laser-Induced Breakdown Spectroscopy Assisted with Phase Transformation Method,” Anal. Chem. 90(11), 7080–7085 (2018).
[Crossref] [PubMed]

Young, T. M.

Yu, H.

R. Yi, X. Yang, R. Zhou, J. Li, H. Yu, Z. Hao, L. Guo, X. Li, Y. Lu, and X. Zeng, “Determination of Trace Available Heavy Metals in Soil Using Laser-Induced Breakdown Spectroscopy Assisted with Phase Transformation Method,” Anal. Chem. 90(11), 7080–7085 (2018).
[Crossref] [PubMed]

P. Zhang, L. Sun, H. Yu, P. Zeng, L. Qi, and Y. Xin, “An Image Auxiliary Method for Quantitative Analysis of Laser-Induced Breakdown Spectroscopy,” Anal. Chem. 90(7), 4686–4694 (2018).
[Crossref] [PubMed]

Yu, J.

E. Negre, V. Motto-Ros, F. Pelascini, and J. Yu, “Classification of plastic materials by imaging laser-induced ablation plumes,” Spectrochim. Acta B At. Spectrosc. 122, 132–141 (2016).
[Crossref]

Yuan, L.

G. Ji, P. Ye, Y. Shi, L. Yuan, X. Chen, M. Yuan, D. Zhu, X. Chen, X. Hu, and J. Jiang, “Laser-Induced Breakdown Spectroscopy for Rapid Discrimination of Heavy-Metal-Contaminated Seafood Tegillarca granosa,” Sensors (Basel) 17(11), 2655 (2017).
[Crossref] [PubMed]

Yuan, M.

G. Ji, P. Ye, Y. Shi, L. Yuan, X. Chen, M. Yuan, D. Zhu, X. Chen, X. Hu, and J. Jiang, “Laser-Induced Breakdown Spectroscopy for Rapid Discrimination of Heavy-Metal-Contaminated Seafood Tegillarca granosa,” Sensors (Basel) 17(11), 2655 (2017).
[Crossref] [PubMed]

Zang, W.

Zeng, P.

P. Zhang, L. Sun, H. Yu, P. Zeng, L. Qi, and Y. Xin, “An Image Auxiliary Method for Quantitative Analysis of Laser-Induced Breakdown Spectroscopy,” Anal. Chem. 90(7), 4686–4694 (2018).
[Crossref] [PubMed]

Zeng, X.

P. Yang, R. Zhou, W. Zhang, R. Yi, S. Tang, L. Guo, Z. Hao, X. Li, Y. Lu, and X. Zeng, “High-sensitivity determination of cadmium and lead in rice using laser-induced breakdown spectroscopy,” Food Chem. 272, 323–328 (2019).
[Crossref]

R. Yi, X. Yang, R. Zhou, J. Li, H. Yu, Z. Hao, L. Guo, X. Li, Y. Lu, and X. Zeng, “Determination of Trace Available Heavy Metals in Soil Using Laser-Induced Breakdown Spectroscopy Assisted with Phase Transformation Method,” Anal. Chem. 90(11), 7080–7085 (2018).
[Crossref] [PubMed]

C. Li, Z. Hao, Z. Zou, R. Zhou, J. Li, L. Guo, X. Li, Y. Lu, and X. Zeng, “Determinations of trace boron in superalloys and steels using laser-induced breakdown spectroscopy assisted with laser-induced fluorescence,” Opt. Express 24(8), 7850–7857 (2016).
[Crossref] [PubMed]

Zeng, X. Y.

P. Yang, R. Zhou, W. Zang, S. S. Tang, Z. Q. Hao, X. Y. Li, Y. F. Lu, and X. Y. Zeng, “Laser-induced breakdown spectroscopy assisted chemometric methods for rice geographic origin classification,” Appl. Opt. 57(28), 8297–8302 (2018).

P. Yang, Y. N. Zhu, X. Y. Yang, J. M. Li, S. S. Tang, Z. Q. Hao, L. B. Guo, X. Y. Li, X. Y. Zeng, and Y. F. Lu, “Evaluation of sample preparation methods for rice geographic origin classification using laser-induced breakdown spectroscopy,” J. Cereal Sci. 80, 111–118 (2018).
[Crossref]

W. T. Li, Y. N. Zhu, X. Li, Z. Q. Hao, L. B. Guo, X. Y. Li, X. Y. Zeng, and Y. F. Lu, “In situ classification of rocks using stand-off laser-induced breakdown spectroscopy with a compact spectrometer,” J. Anal. At. Spectrom. 33(3), 461–467 (2018).
[Crossref]

Zhang, C.

C. Zhang, T. Shen, F. Liu, and Y. He, “Identification of Coffee Varieties Using Laser-Induced Breakdown Spectroscopy and Chemometrics,” Sensors (Basel) 18(2), 95 (2017).
[Crossref] [PubMed]

Zhang, P.

P. Zhang, L. Sun, H. Yu, P. Zeng, L. Qi, and Y. Xin, “An Image Auxiliary Method for Quantitative Analysis of Laser-Induced Breakdown Spectroscopy,” Anal. Chem. 90(7), 4686–4694 (2018).
[Crossref] [PubMed]

Zhang, W.

P. Yang, R. Zhou, W. Zhang, R. Yi, S. Tang, L. Guo, Z. Hao, X. Li, Y. Lu, and X. Zeng, “High-sensitivity determination of cadmium and lead in rice using laser-induced breakdown spectroscopy,” Food Chem. 272, 323–328 (2019).
[Crossref]

Zhang, Y.

C. Cai, Y. Wang, Z. Cao, Y. Zhang, T. Lu, and D. Wang, “HOG pedestrian detection based on edge symmetry and trilinear interpolation,” 7 (2018).

Zhou, R.

P. Yang, R. Zhou, W. Zhang, R. Yi, S. Tang, L. Guo, Z. Hao, X. Li, Y. Lu, and X. Zeng, “High-sensitivity determination of cadmium and lead in rice using laser-induced breakdown spectroscopy,” Food Chem. 272, 323–328 (2019).
[Crossref]

R. Yi, X. Yang, R. Zhou, J. Li, H. Yu, Z. Hao, L. Guo, X. Li, Y. Lu, and X. Zeng, “Determination of Trace Available Heavy Metals in Soil Using Laser-Induced Breakdown Spectroscopy Assisted with Phase Transformation Method,” Anal. Chem. 90(11), 7080–7085 (2018).
[Crossref] [PubMed]

P. Yang, R. Zhou, W. Zang, S. S. Tang, Z. Q. Hao, X. Y. Li, Y. F. Lu, and X. Y. Zeng, “Laser-induced breakdown spectroscopy assisted chemometric methods for rice geographic origin classification,” Appl. Opt. 57(28), 8297–8302 (2018).

C. Li, Z. Hao, Z. Zou, R. Zhou, J. Li, L. Guo, X. Li, Y. Lu, and X. Zeng, “Determinations of trace boron in superalloys and steels using laser-induced breakdown spectroscopy assisted with laser-induced fluorescence,” Opt. Express 24(8), 7850–7857 (2016).
[Crossref] [PubMed]

Zhu, D.

G. Ji, P. Ye, Y. Shi, L. Yuan, X. Chen, M. Yuan, D. Zhu, X. Chen, X. Hu, and J. Jiang, “Laser-Induced Breakdown Spectroscopy for Rapid Discrimination of Heavy-Metal-Contaminated Seafood Tegillarca granosa,” Sensors (Basel) 17(11), 2655 (2017).
[Crossref] [PubMed]

Zhu, Y. N.

W. T. Li, Y. N. Zhu, X. Li, Z. Q. Hao, L. B. Guo, X. Y. Li, X. Y. Zeng, and Y. F. Lu, “In situ classification of rocks using stand-off laser-induced breakdown spectroscopy with a compact spectrometer,” J. Anal. At. Spectrom. 33(3), 461–467 (2018).
[Crossref]

P. Yang, Y. N. Zhu, X. Y. Yang, J. M. Li, S. S. Tang, Z. Q. Hao, L. B. Guo, X. Y. Li, X. Y. Zeng, and Y. F. Lu, “Evaluation of sample preparation methods for rice geographic origin classification using laser-induced breakdown spectroscopy,” J. Cereal Sci. 80, 111–118 (2018).
[Crossref]

Zou, Z.

Adv. Mat. Res. (1)

H. Y. Kong, L. X. Sun, J. T. Hu, Y. Xin, and Z. B. Cong, “Quantitative Analysis of Steels Using PLS with Three Data Reduction Methods Based on LIBS,” Adv. Mat. Res. 997, 578–582 (2014).

Anal. Bioanal. Chem. (1)

J. L. Gottfried, “Discrimination of biological and chemical threat simulants in residue mixtures on multiple substrates,” Anal. Bioanal. Chem. 400(10), 3289–3301 (2011).
[Crossref] [PubMed]

Anal. Chem. (2)

R. Yi, X. Yang, R. Zhou, J. Li, H. Yu, Z. Hao, L. Guo, X. Li, Y. Lu, and X. Zeng, “Determination of Trace Available Heavy Metals in Soil Using Laser-Induced Breakdown Spectroscopy Assisted with Phase Transformation Method,” Anal. Chem. 90(11), 7080–7085 (2018).
[Crossref] [PubMed]

P. Zhang, L. Sun, H. Yu, P. Zeng, L. Qi, and Y. Xin, “An Image Auxiliary Method for Quantitative Analysis of Laser-Induced Breakdown Spectroscopy,” Anal. Chem. 90(7), 4686–4694 (2018).
[Crossref] [PubMed]

Appl. Opt. (2)

Food Chem. (2)

S. Moncayo, S. Manzoor, J. D. Rosales, J. Anzano, and J. O. Caceres, “Qualitative and quantitative analysis of milk for the detection of adulteration by Laser Induced Breakdown Spectroscopy (LIBS),” Food Chem. 232, 322–328 (2017).
[Crossref] [PubMed]

P. Yang, R. Zhou, W. Zhang, R. Yi, S. Tang, L. Guo, Z. Hao, X. Li, Y. Lu, and X. Zeng, “High-sensitivity determination of cadmium and lead in rice using laser-induced breakdown spectroscopy,” Food Chem. 272, 323–328 (2019).
[Crossref]

IEEE Trans. Neural Netw. (1)

C. W. Hsu and C. J. Lin, “A comparison of methods for multiclass support vector machines,” IEEE Trans. Neural Netw. 13(2), 415–425 (2002).
[Crossref] [PubMed]

Indonesian Journal of Electrical Engineering and Computer Science (1)

A. Sophian and D. Aini, “Fingertip Detection Using Histogram of Gradients and Support Vector Machine,” Indonesian Journal of Electrical Engineering and Computer Science 8, 482–486 (2017).

Int. J. Comput. Appl. (1)

S. J. M. Rad, F. A. Tab, and K. Mollazade, “Application of imperialist competitive algorithm for feature selection a case study on bulk rice classification,” Int. J. Comput. Appl. 40(1), 41–48 (2012).

International Journal of Grid and Utility Computing (1)

Y. Wang, J. Du, X. Cheng, Z. Liu, and K. Lin, “Degradation and encryption for outsourced PNG images in cloud storage,” International Journal of Grid and Utility Computing 7(1), 22–28 (2016).
[Crossref]

J. Anal. At. Spectrom. (2)

J. Kang, R. Li, Y. Wang, Y. Chen, and Y. Yang, “Ultrasensitive detection of trace amounts of lead in water by LIBS-LIF using a wood-slice substrate as a water absorber,” J. Anal. At. Spectrom. 32(11), 2292–2299 (2017).
[Crossref]

W. T. Li, Y. N. Zhu, X. Li, Z. Q. Hao, L. B. Guo, X. Y. Li, X. Y. Zeng, and Y. F. Lu, “In situ classification of rocks using stand-off laser-induced breakdown spectroscopy with a compact spectrometer,” J. Anal. At. Spectrom. 33(3), 461–467 (2018).
[Crossref]

J. Cereal Sci. (1)

P. Yang, Y. N. Zhu, X. Y. Yang, J. M. Li, S. S. Tang, Z. Q. Hao, L. B. Guo, X. Y. Li, X. Y. Zeng, and Y. F. Lu, “Evaluation of sample preparation methods for rice geographic origin classification using laser-induced breakdown spectroscopy,” J. Cereal Sci. 80, 111–118 (2018).
[Crossref]

Laser Journal (2)

H. Li, Y. E. Wang, Q. Liu, and D. H. Xu, “Varieties discrimination of rice seed based on laser induced breakdown spectroscopy of subsection combination,” Laser Journal 38, 8–12 (2017).

Z. Q. Ke, Y. E. Wang, H. Fan, Q. Li, Liu, and J. H. Lin,”Identification of Rice Seed Varieties Based on LIBS,” Laser Journal 37, 56–60 (2016).

Neural Comput. (1)

H. T. Lin and C. J. Lin, “A Study on Sigmoid Kernels for SVM and the Training of non-PSD Kernels by SMO-type Methods,” Neural Comput. 3, 1–32 (2003).

Opt. Express (1)

Pattern Recognit. (1)

S. A. M. Al-Sumaidaee, M. A. M. Abdullah, R. R. O. Al-Nima, S. S. Dlay, and J. A. Chambers, “Multi-gradient features and elongated quinary pattern encoding for image-based facial expression recognition,” Pattern Recognit. 71, 249–263 (2017).
[Crossref]

Proc. SPIE (1)

T. Karpate, S. K. M. Muhammed, R. Nayak, V. K. Unnikrishnan, and C. Santhosh, “LIBS: a potential tool for industrial/agricultural waste water analysis,” Proc. SPIE 9893, 989317 (2016).
[Crossref]

Sensors (Basel) (2)

G. Ji, P. Ye, Y. Shi, L. Yuan, X. Chen, M. Yuan, D. Zhu, X. Chen, X. Hu, and J. Jiang, “Laser-Induced Breakdown Spectroscopy for Rapid Discrimination of Heavy-Metal-Contaminated Seafood Tegillarca granosa,” Sensors (Basel) 17(11), 2655 (2017).
[Crossref] [PubMed]

C. Zhang, T. Shen, F. Liu, and Y. He, “Identification of Coffee Varieties Using Laser-Induced Breakdown Spectroscopy and Chemometrics,” Sensors (Basel) 18(2), 95 (2017).
[Crossref] [PubMed]

Spectrochim. Acta B At. Spectrosc. (3)

E. Negre, V. Motto-Ros, F. Pelascini, and J. Yu, “Classification of plastic materials by imaging laser-induced ablation plumes,” Spectrochim. Acta B At. Spectrosc. 122, 132–141 (2016).
[Crossref]

Z. Chen, H. Li, M. Liu, and R. Li, “Fast and sensitive trace metal analysis in aqueous solutions by laser-induced breakdown spectroscopy using wood slice substrates,” Spectrochim. Acta B At. Spectrosc. 63(1), 64–68 (2008).
[Crossref]

G. S. Senesi, B. Campanella, E. Grifoni, S. Legnaioli, G. Lorenzetti, S. Pagnotta, F. Poggialini, V. Palleschi, and O. De Pascale, “Elemental and mineralogical imaging of a weathered limestone rock by double-pulse micro-Laser-Induced Breakdown Spectroscopy,” Spectrochim. Acta B At. Spectrosc. 143, 91–97 (2018).
[Crossref]

Other (7)

M. Sweetapple, S. Tassios, and D. Body, “In situ analysis and mapping of lithium in Li-bearing pegmatite minerals By Laser-Induced Breakdown Spectroscopy (LIBS),” in PEG2015 poster, pp.105–106.

M. Zhang, “Eeg feature extraction based on non-negative matrix factorization,” (Yanshan University 2014).

C. W. Hsu and C. J. Lin, “A pratical guide for support vector matchine,” 1–16 (2003).

N. Dalal and B. Triggs, “Histograms of oriented gradients for human detection,” IEEE Computer Society Conference on Computer Vision and Pattern Recognition (IEEE, 2005), pp. 886–893.

N. Dalal, B. Triggs, and C. Schmid, “Human Detection Using Oriented Histograms of Flow and Appearance,” in Computer Vision – ECCV 2006 (Springer Berlin Heidelberg, 2006), 428–441.

C. Cai, Y. Wang, Z. Cao, Y. Zhang, T. Lu, and D. Wang, “HOG pedestrian detection based on edge symmetry and trilinear interpolation,” 7 (2018).

R. Kadota, H. Sugano, M. Hiromoto, H. Ochi, R. Miyamoto, and Y. Nakamura, “Hardware Architecture for HOG Feature Extraction,” in 2009 Fifth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, 2009), 1330–1333.

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Figures (5)

Fig. 1
Fig. 1 LIBS experimental setup.
Fig. 2
Fig. 2 Schematic diagram of characteristics spectrum conversion to characteristics images
Fig. 3
Fig. 3 (a). The relationship between the number of image columns and the classification accuracy (b). The relationship between grayscale coefficient and the classification accuracy.
Fig. 4
Fig. 4 Comparison of classification results using FSIM (a) and IHFM (b).
Fig. 5
Fig. 5 Classification result comparison of FSIM and IHFM for other samples.

Tables (2)

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Table 1 Rice samples information list

Tables Icon

Table 2 Classification accuracies of FSIM and IHFM for 24 varieties of rice samples

Equations (3)

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g = I ( X , Y ) H ( X , Y )
ρ X Y = C o v ( X , Y ) σ X σ Y
C o v ( X , Y ) = E [ ( X - μ X ) ( Y - μ Y ) ]

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