Uncovering Vein Patterns from Color Skin Images for Forensic Analysis

Abstract

Recent technological advances have allowed for a proliferation of digital evidence images. Using these images as evidence in legal cases (e.g. child sexual abuse, child pornography and masked gunmen) can be very challenging, because the faces of criminals or victims are not visible. Although large skin marks and tattoos have been used, they are ineffective in some legal cases, because the skin exposed in evidence images neither have unique tattoos nor enough skin marks for identification. The blood vessel between the skin and the muscle covering most parts of the human body is a powerful biometric trait, because of its universality, permanence and distinctiveness. Traditionally, it was impossible to use vein patterns for forensic identification, because they were not visible in color images. This paper proposes an algorithm to uncover vein patterns from the skin exposed in color images for personal identification. Based on the principles of optics and skin biophysics, we modeled the inverse process of skin color formation in an image and derived spatial distributions of biophysical parameters from color images, where vein patterns can be observed. Experimental results are very encouraging. The clarity of the vein patterns in resultant images is comparable to or even better than that in near infrared images.

Cite

Text

Tang et al. "Uncovering Vein Patterns from Color Skin Images for Forensic Analysis." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2011. doi:10.1109/CVPR.2011.5995531

Markdown

[Tang et al. "Uncovering Vein Patterns from Color Skin Images for Forensic Analysis." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2011.](https://mlanthology.org/cvpr/2011/tang2011cvpr-uncovering/) doi:10.1109/CVPR.2011.5995531

BibTeX

@inproceedings{tang2011cvpr-uncovering,
  title     = {{Uncovering Vein Patterns from Color Skin Images for Forensic Analysis}},
  author    = {Tang, Chaoying and Kong, Adams Wai-Kin and Craft, Noah},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2011},
  pages     = {665-672},
  doi       = {10.1109/CVPR.2011.5995531},
  url       = {https://mlanthology.org/cvpr/2011/tang2011cvpr-uncovering/}
}