Plastic identification by remote sensing spectroscopic NIR imaging using kernel partial least squares (KPLS)

Chemometrics and Intelligent Laboratory Systems

Volumn 35, Issue 2, 1996, Pages 187-197

  Van Den Broek, W H A M ^a   Derks, E P P A ^a   Van De Ven, E W ^a   Wienke, D ^a   Geladi, P ^b   Buydens, L M C ^a  

^a RADBOUD UNIVERSITY NIJMEGEN   (Netherlands)

^b UMEÅ UNIVERSITY   (Sweden)

Author keywords

kernel PLS; multivariate image analysis; NIR imaging

Indexed keywords

ARTICLE; CHEMOMETRICS; CLASSIFICATION; INFRARED SPECTROSCOPY; PRIORITY JOURNAL; STATISTICS;

EID: 0030475040     PISSN: 01697439     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0169-7439(96)00056-1     Document Type: Article

References (24)

1. [1] P. Geladi and B.R. Kowalski, Partial Least Squares Regression: A Tutorial, Analytica Chimica Acta 185 (1986) 1-17.
2. [2] I.E. Frank and J.H. Friedman, A statistical view of some chemometrics regression tools, Technometrics 35 (1993) 109-148.
3. [3] I. Helland, Partial Least Squares Regression and Statistical Models, Scand. J. Stat. 17 (1990) 97-114.
4. [4] R. Vong, P. Geladi, S. Wold and K. Esbensen, Source Contributions to ambient aerosol calculated by discriminant Partial least squares regression (PLS), J. Chemom. 2 (1988) 281-296.
5. [5] H. Martens and T. Naes, Multivariate Calibration by Data Compression, in: Near-Infrared Technology in the Agricultural and Food Industries, P. Williams and K. Morris (Eds.) (American Association of Cereal Chemists, 1990).
6. [6] F. Lindgren, Third Generation PLS: some Elements and Applications, Thesis Umeå University, Research Group for Chemometrics, Umeå, Sweden, 1994.
7. [7] S. de Jong and C.J.F. ter Braak, Short Communication: Comments on the PLS Kernel Algorithm, J. Chemom. 8 (1994) 169-174.
8. [8] G. Holzhey, Das Duale System und seine Auswirkungen, Papier 47 (1993) 337-344.
9. [9] H. Ritzmann and D. Schudel, Kunststoffabfalle automatisch sortieren, Kunststoffe 84 (1994) 582-584.
10. [10] N. Eisenreich, Schnelle Identifikation von Kunststoffen mit schneller nahinfrarotspektroskopie, in: 23rd Int. Annual Conf. of ICT 1992: Waste management of energetic materials and polymers, June 30-July 3, 1992, Karlsruhe, Germany, pp. 59.1-59.12.
11. [11] Th. Huth-Fehre, R. Feldhoff, Th. Kantimm, L. Quick, F. Winter, K. Camman, W. van den Broek, D. Wienke, W. Melssen and L. Buydens, NIR-Remote Sensing and Artificial Neural Networks for Rapid Identification of Post Consumer Plastics, J. Mol. Struct. 348 (1995) 143-146.
12. [12] M.K. Alam, S.L. Stanton and G.A Hebner, Near-Infrared Spectroscopy and Neural Networks for Resin Identification, Spectroscopy 9 (1994) 30-35.
13. [13] D.M. Scott and R.L. Waterland, Identification of Plastic Waste Using Spectroscopy and Neural Networks, Polym. Eng. Sci. 35 (1995) 1011-1015.
14. [14] W.H.A.M. van den Broek, D. Wienke, W.J. Melssen, C.W.A. de Crom and L.M.C Buydens, Identification of Plastics among non-plastics in Mixed Waste by Remote Sensing Near-Infrared Imaging Spectroscopy. 1. Image Improvement and Analysis by Singular Value Decomposition, Anal. Chem. 67 (1995) 3753-3759.
15. [15] D. Wienke, W.H.A.M. van den Broek and L.M.C. Buydens, Identification of Plastics among non-plastics in Mixed Waste by Remote Sensing Near-Infrared Imaging Spectroscopy. 2. Multivariate Image Rank Analysis for Rapid Classification, Anal. Chem. 67 (1995) 3760-3766.
16. [16] W.H.A.M. van den Broek, D. Wienke, J.C.A. Kraak, W.J. Melssen, and L.M.C. Buydens, Filter selection by Genetic Algorithms for spectroscopic NIR Imaging, to be submitted.
17. [17] E.N. Lewis, P.J. Treado, R.C. Reeder, G.M. Story, A.E. Dowrey, C. Marcott and I.W. Levin, Fourier Transform Spectroscopic Imaging Using an Infrared Focal-Plane Array Detector, Anal. Chem. 67 (1995) 3377-3381.
18. [18] P.T. Treado. I.W. Levin and E.N. Lewis, Indium Antimonide (InSb) Focal Plane Array (FPA) Detection for Near-Infrared Imaging Microscopy, Appl. Spectrosc. 48 (1994) 607-615.
19. [19] B. Novales, D. Bertrand, M.F. Devaux and P. Robert, Assessment of the quality of wheat milling products by fluorescence video imaging, Int. Conf. on Quality Control by Artificial Vision, May 17-19th, 1995, Le Creusot, France.
20. [20] E.N. Lewis and I.W. Levin, Vibrational Spectroscopic Microscopy: Raman, Near-Infrared and Mid-Infrared Imaging Techniques, JMSA 1 (1995) 35-46.
21. [21] S. Wold, Cross-Validatory Estimation of the Number of Components in Factor and Principal Components Models, Technometrics 20 (1978) 397-405.
22. [22] D.W. Osten, Selection of optimal regression models via cross-validation, J. Chemom. Int. Lab. Syst. 2 (1988) 39-48.
23. [23] W.R. Dillon and M. Goldstein, in: Multivariate Analysis, Methods and Applications (John Wiley and Sons, New York, 1984).
24. [24] W.H.A.M. van den Broek, D. Wienke, E.W. van de Ven, W.J. Melssen, R. Feldhoff, T. Huth-Fehre, T. Kantimm and L.M.C. Buydens, Application of a Spectroscopic Infrared Focal Plane Array (FPA) Sensor for On-line Identification of Plastic Waste, to be submitted.