• Laser & Optoelectronics Progress
  • Vol. 58, Issue 6, 6000071 (2021)
Sun Wei1, Chen Ruili1、*, and Luo Jianxin2
Author Affiliations
  • 1College of Investigation, People''s Public Security University of China, Beijing 100038, China
  • 2Institute of Criminal Science and Technology, Public Security Bureau of Zhengzhou, Zhengzhou, Henan 450016, China
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    DOI: 10.3788/LOP202158.0600007 Cite this Article Set citation alerts
    Sun Wei, Chen Ruili, Luo Jianxin. Review of Research on Hyperspectral Imaging Technology Applied to Bloodstain Detection Applications[J]. Laser & Optoelectronics Progress, 2021, 58(6): 6000071 Copy Citation Text show less

    Abstract

    Bloodstain is a biological examination material with high occurrence rate in the scene of violent cases. Inspection and identification work can provide a lot of information for the rapid detection of these cases. Hyperspectral imaging technology can be used for nondestructive and rapid imaging of bloodstains in crime scenes. Compared with the chemical reagent method and traditional spectral analysis method for bloodstain detection, the characteristic of image-spectrum merging is a significant advantage of hyperspectral imaging technology. Based on the brief analysis of the characteristics of hyperspectral imaging, data expression, and data processing methods, this paper introduces the applications of hyperspectral imaging technology in the fields such as national defense, ecology, and food. This paper focuses on the application status of hyperspectral imaging technology as a technical means of bloodstain detection in potential bloodstain appearance, bloodstain component analysis, bloodstain classification and identification, and bloodstain age prediction. The paper summarizes the challenges encountered in the application process and the later key research directions and development prospects.
    Sun Wei, Chen Ruili, Luo Jianxin. Review of Research on Hyperspectral Imaging Technology Applied to Bloodstain Detection Applications[J]. Laser & Optoelectronics Progress, 2021, 58(6): 6000071
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