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The application of near-infrared reflectance hyperspectral imaging for the detection and extraction of bloodstains

Cluster Computing volume 22, pages 8453–8461 (2019)Cite this article

Abstract

Blood is not only the traces of the murder scene but also the evidence, has a very important role in the acquisition of criminal evidence and forensic identification. However, the conventional testing methodology being currently deployed in bloodstain identification may destruct the human DNA. Some investigators used the method is undeserved, often regret in the exploration of the scene. From this point of view, efficient non-destructive technology for quickly identifying bloodstain is an emerging issue in this field. In this article, a method is proposed for nondestructive testing of identifying blood stains, and design a blood model named blood band inequality model to extract blood from eight kinds of suspected blood. The validity of the model was verified by the theory and experiment. Extraction efficiency of blood is as high as 94.71%, and the omission rate is only 5.29%. Experiments proved hyperspectral imaging can be used for the non-contact detection, identification of blood stains and the new model is effective in the extraction of blood.

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Acknowledgements

The research work is supported by National Natural Science foundation of China under Grant No. 81400285. And the authors would also like to gratefully acknowledge the support from the key research and development foundation of Shandong Province under Grant No. 2016GGX101016.

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Authors and Affiliations

  1. College of Physics and Electronics, Shandong Normal University, Jinan, China

    Yuefeng Zhao, Nannan Hu, Yunuan Wang, Yonglei Liu, Xiaofei Li & Jingjing Wang

Authors
  1. Yuefeng Zhao
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  2. Nannan Hu
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  3. Yunuan Wang
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  4. Yonglei Liu
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  5. Xiaofei Li
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  6. Jingjing Wang
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Correspondence to Yuefeng Zhao, Xiaofei Li or Jingjing Wang.

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Zhao, Y., Hu, N., Wang, Y. et al. The application of near-infrared reflectance hyperspectral imaging for the detection and extraction of bloodstains. Cluster Comput 22, 8453–8461 (2019). https://doi.org/10.1007/s10586-018-1869-9

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  • DOI: https://doi.org/10.1007/s10586-018-1869-9

Keywords

  • Hyperspectral imaging
  • Blood stains extraction
  • BBIM