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Formation Pattern Classification of Paper based on Imaging using Multiple Light Sources


Ka Young Lee*, Seongho Lim, Youngsoo Lee and Young Bin Pyo

The analysis and identification of paper is a major research topic in the field of forensic document examination. Damage to documents serving as test specimens must be reduced to a minimum; thus, a non-destructive analysis method must be used for analyzing the paper that comprises the documents. Various non-destructive analysis and identification methods are currently being developed for this purpose. Herein, multiple light sources were used to perform non-destructive optical inspection of office paper specimens of major brands used in South Korea to verify the possibility of analysis and identification. Additionally, the images obtained through the non-destructive analysis were applied in a deep learning algorithm to test whether paper specimens from the same brand could be automatically classified.

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