Development of Discriminant Analyzing System for Waste Wood Products using Chemometrical NIR Imaging Technique

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In this study, we developed new discriminant analysis named NIR chemometrical imaging, and examined the feasibility of the technique for wood wastes. Vis and NIR images of sample were captured by vidicon camera, and cumulative histogram was constructed from corrected difference luminance brightness of sample and gray plate. SIMCA analysis was performed for three kinds of wood wastes where cumulative histograms as pseudo-spectral information.The results of SIMCA analysis showed high correct classification of over 80% for all categories, and average correct classification was 88.9%. Discriminating power for SIMCA analysis indicated that visible image (600-800 nm) is effective for classifying non-treated wood, and NIR image (1600-1800 nm) is effective for classifying overlaid and non-treated wood, respectively. These results suggest that the new optical system should be applicable as online monitoring system of recycling mill for wood waste.