Abstract
The war on drug abuse involves all nations worldwide. Normally, molecular components are unique, and thus the drugs can be identified based on it. However, this procedure started to be more unreliable with the introduction of new ATS molecular structures which are increasingly complex and sophisticated. Hence, unique characteristics of molecular structure of ATS drug must be accurately identified. Therefore, this paper is meant for formulating an exact 3D geometric moment invariants to represent the drug molecular structure. The performance of the proposed technique was analyzed using drug chemical structures obtained from United Nations Office of Drugs and Crime (UNODC) and also from various sources. The evaluation shows the technique is qualified to be further explored and adapted in the future works to be fully compatible with ATS drug identification domain.
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References
Langman, L.J., Bowers, L.D., Collins, J.A., Hammett-Stabler, C.A., LeBeau, M.A.: Gas Chromatography/Mass Spectrometry Confirmation of Drugs; Approved Guidelines, 2nd edn. Clinical and Laboratory Standards Institute, Pennsylvania (2010)
Langman, L.J., Bowers, L.D., Collins, J.A., Hammett-Stabler, C.A., LeBeau, M.A.: Gas Chromatography/Mass Spectrometry Confirmation of Drugs; Approved Guidelines, 2nd edn. In: Clinical and Laboratory Standards Institute, Pennsylvania (2010)
Lin, D.-L., Yin, R.-M., Ray, L.H.: Gas Chromatography-mass spectrometry (gc-ms) analysis of amphetamine, methamphetamine, 3,4-Methylenedioxyamphetamine and 3,4-methylenedioxymethamphetamine in human hair and hair sections. J. Food Drug Anal. 13(3), 193–200 (2005)
McShane, J.J.: GC-MS is Not Perfect: The Case Study of Methamphetamine (2011)
International Union of Pure and Applied Chemistry: Compendium of Chemical Terminology. Gold Book, 2nd edn. Blackwell Scientific Publications, Oxford (2006)
Mendelson, J., Uemura, N., Harris, D., Nath, R.P., Fernandez, E., Jacob, P., Everhart, E.T., Jones, R.T.: Human Pharmacology of the methamphetamine stereoisomers. Clin. Pharmacol. Ther. 80(4), 403–420 (2006)
Todeschini, R., Consonni, V.: Descriptors from molecular geometry. In: Handbook of Chemoinformatics. pp. 1004–1033. Wiley-VCH Verlag GmbH (2008)
Muda, A.K.: Authorship Invarianceness for Writer Identification Using Invariant Discretization and Modified Immune Classifier. Universiti Teknologi Malaysia (2009)
Sun, Y., Liu, W., Wang, Y.: United moment invariants for shape discrimination. In: International Conference on Robotics, Intelligent Systems and Signal Processing, Changsha, pp. 88–93. IEEE (2003)
Hu, M.K.: Visual pattern recognition by moment invariants. In: IRE Transactions on Information Theory 1962, pp. 179–187
Sadjadi, F.A., Hall, E.L.: Three-dimensional moment invariants. pattern analysis and machine intelligence. IEEE Trans. PAMI-2 2, 127–136 (1980). doi:10.1109/TPAMI.1980.4766990
Flusser, J., Suk, T., Zitová, B.: Moments and Moment Invariants in Pattern Recognition, vol. 1. John Wiley and Sons Ltd, West Sussex (2009)
Hosny, K.M.: Exact and fast computation of geometric moments for gray level images. Appl. Math. Comput. 189(2), 1214–1222 (2007). doi:10.1016/j.amc.2006.12.025
Yap, P.-T., Paramesran, R.: An efficient method for the computation of legendre moments. IEEE Trans. Pattern Anal. Mach. Intell. 27(12), 1996–2002 (2005). doi:10.1109/tpami.2005.232
Suk, T., Flusser, J.: Tensor Method for constructing 3D moment invariants. In: Berciano, A., DÃaz-Pernil, D., Kropatsch, W.G., Molina-Abril, H., Real, P. (eds.) Computer Analysis of Images and Patterns, Sevilla, Spain, pp. 213–219. Springer, Berlin (2011)
Liao, S.X., Pawlak, M.: On image analysis by moments. IEEE Trans. Pattern Anal. Mach. Intell. 18(3), 254–266 (1996). doi:10.1109/34.485554
Xu, D., Li, H.: Geometric moment invariants. Pattern Recogn. 41(1), 240–249 (2008)
ChemAxon.: Marvin. http://www.chemaxon.com (2014)
Jmol.: Jmol: an open-source Java viewer for chemical structures in 3D. http://www.jmol.org/ (2014)
Min, P.: http://www.cs.princeton.edu/~min/binvox (2014)
Breiman, L.: Random Forests. Machine Learning, 5–32 (2001)
Razali, N.M., Yap, B.W.: Power Comparisons of shapiro-wilk, kolmogorov-smirnov, lilliefors and anderson-darling tests. J. Stat. Model. Analytics 2(1), 21–33 (2011)
Acknowledgments
This work was supported by Collaborative Research Programme (CRP) – ICGEB Research Grant (CRP/MYS13-03) from International Centre for Genetic Engineering and Biotechnology (ICGEB), Italy and Universiti Teknikal Malaysia Melaka, UTeM.
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Pratama, S.F., Muda, A.K., Choo, YH., Abraham, A. (2016). Exact Computation of 3D Geometric Moment Invariants for ATS Drugs Identification. In: Snášel, V., Abraham, A., Krömer, P., Pant, M., Muda, A. (eds) Innovations in Bio-Inspired Computing and Applications. Advances in Intelligent Systems and Computing, vol 424. Springer, Cham. https://doi.org/10.1007/978-3-319-28031-8_30
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DOI: https://doi.org/10.1007/978-3-319-28031-8_30
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