Laser-induced breakdown spectroscopy (LIBS) combined with support vector machine (SVM) algorithm was used to identify 11 kinds of plastics. For each plastic, 100 spectra recorded by the spectrometer system were divided equally into training set and test set, and the former was used to train SVM model while the latter was used to validate SVM model created by the training set. Result shows that 543 of 550 test set spectra are identified correctly with the average correct identification rate 98.73%. However, there are six spectra of PU misidentified as PMMA. This is because the difference of nitrogen content in 11 plastics cannot be reflected by the intensities of N I 746.87 nm and C-N (0,0) 388.3 nm due to the influence of ambient air. Methods and reference data are provided for further study of plastics identification by laser-induced breakdown spectroscopy technique.

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Adaptive infrared image contrast enhancement is presented based on modified particle swarm optimization (PSO) and incomplete Beta Function. On the basis of traditional PSO, modified PSO integrates into the theory of Multi-Particle Swarm and evolution theory algorithm. By using separate search space optimal solution of multiple particles, the global search ability is improved. And in the iteration procedures, timely adjustment of acceleration coefficients is convenient for PSO to find the global optimal solution in the later iteration. Through infrared image simulation, experimental results show that the modified PSO is better than the standard PSO in computing speed and convergence.