Infrared and Laser Engineering, Volume. 49, Issue 6, 20201011(2020)

Study on UV polarization reflection characteristics of sweat latent fingerprints(Invited)

Wang Feng1...2, Jia Rong1,2,*, Liu Xiao1,2, Zhai Hao1,2, Wang Sunchen1,2, and Wu Yunzhi12 |Show fewer author(s)
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    Sweat latent fingerprint was the most common type of fingerprint on crime scenes, featuring features that disappeared quickly and were not easily detected. According to its characteristics, the UV polarization imaging detection technology was used for target detection. Compared with the traditional intensity image, the polarization parameter image could improve the target contrast and help to distinguish the targets in different backgrounds. However, the UV polarization imaging detection technology was sensitive to angles, bands and guest materials. Therefore, through the design of reasonable experiments, the characteristics of the UV polarization reflection characteristics of the sweat latent fingerprints with angle, band and guest materials were analyzed. The results show that the sweat latent fingerprints exhibited regular polarization characteristics at different angles; among the four spectral polarization channels provided by the system, the near-ultraviolet bands are well reproducible and distinguishable; the polarization characteristics of different guest materials varied greatly. The UV-polarized reflection characteristics of the comparative analysis samples effectively improved the detection and recognition performance of latent fingerprints, and provided a basis for the UV-polarized imaging detection technology of sweat latent fingerprints.

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    Wang Feng, Jia Rong, Liu Xiao, Zhai Hao, Wang Sunchen, Wu Yunzhi. Study on UV polarization reflection characteristics of sweat latent fingerprints(Invited)[J]. Infrared and Laser Engineering, 2020, 49(6): 20201011

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    Paper Information

    Category: Special issue-Polarization detection and imaging

    Received: Mar. 5, 2020

    Accepted: Apr. 20, 2020

    Published Online: Sep. 21, 2020

    The Author Email: Rong Jia (jr2803114834@163.com)

    DOI:10.3788/irla20201011

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