Matching vein patterns from color images for forensic investigation
Child sexual abuse is a serious global problem and has gained public attention in recent years. Due to the popularity of digital cameras, many perpetrators take images of their sexual activities with child victims. Traditionally, it was difficult to use cutaneous vascular patterns for forensic ident...
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sg-ntu-dr.10356-839362020-05-28T07:18:08Z Matching vein patterns from color images for forensic investigation Zhang, Hengyi Tang, Chaoying Kong, Adams Wai-Kin Craft, Noah School of Computer Engineering IEEE International Conference On Biometrics: Theory, Applications And Systems (5th : 2012 : Arlington, Virginia, US) DRNTU::Engineering::Computer science and engineering Child sexual abuse is a serious global problem and has gained public attention in recent years. Due to the popularity of digital cameras, many perpetrators take images of their sexual activities with child victims. Traditionally, it was difficult to use cutaneous vascular patterns for forensic identification, because they were nearly invisible in color images. Recently, this limitation was overcome using a computational method based on an optical model to uncover vein patterns from color images for forensic verification. This optical-based vein uncovering (OBVU) method is sensitive to the power of the illuminant and does not utilize skin color in images to obtain training parameters to optimize the vein uncovering performance. Prior publications have not included an automatic vein matching algorithm for forensic identification. As a result, the OBVU method only supported manual verification. In this paper, we propose two new schemes to overcome limitations in the OBVU method. Specifically, a color optimization scheme is used to derive the range of biophysical parameters to obtain training parameters and an automatic intensity adjustment scheme is used to enhance the robustness of the vein uncovering algorithm. We also developed an automatic matching algorithm for vein identification. This algorithm can handle rigid and non-rigid deformations and has an explicit pruning function to remove outliers in vein patterns. The proposed algorithms were examined on a database with 300 pairs of color and near infrared (NIR) images collected from the forearms of 150 subjects. The experimental results are encouraging and indicate that the proposed vein uncovering algorithm performs better than the OBVU method and that the uncovered patterns can potentially be used for automatic criminal and victim identification. 2013-07-22T06:13:51Z 2019-12-06T15:34:55Z 2013-07-22T06:13:51Z 2019-12-06T15:34:55Z 2012 2012 Conference Paper Zhang, H., Tang, C., Kong, A. W.-K., & Craft, N. (2012). Matching vein patterns from color images for forensic investigation. 2012 IEEE Fifth International Conference on Biometrics: Theory, Applications and Systems (BTAS). https://hdl.handle.net/10356/83936 http://hdl.handle.net/10220/11981 10.1109/BTAS.2012.6374560 en © 2012 IEEE. |
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DRNTU::Engineering::Computer science and engineering Zhang, Hengyi Tang, Chaoying Kong, Adams Wai-Kin Craft, Noah Matching vein patterns from color images for forensic investigation |
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Child sexual abuse is a serious global problem and has gained public attention in recent years. Due to the popularity of digital cameras, many perpetrators take images of their sexual activities with child victims. Traditionally, it was difficult to use cutaneous vascular patterns for forensic identification, because they were nearly invisible in color images. Recently, this limitation was overcome using a computational method based on an optical model to uncover vein patterns from color images for forensic verification. This optical-based vein uncovering (OBVU) method is sensitive to the power of the illuminant and does not utilize skin color in images to obtain training parameters to optimize the vein uncovering performance. Prior publications have not included an automatic vein matching algorithm for forensic identification. As a result, the OBVU method only supported manual verification. In this paper, we propose two new schemes to overcome limitations in the OBVU method. Specifically, a color optimization scheme is used to derive the range of biophysical parameters to obtain training parameters and an automatic intensity adjustment scheme is used to enhance the robustness of the vein uncovering algorithm. We also developed an automatic matching algorithm for vein identification. This algorithm can handle rigid and non-rigid deformations and has an explicit pruning function to remove outliers in vein patterns. The proposed algorithms were examined on a database with 300 pairs of color and near infrared (NIR) images collected from the forearms of 150 subjects. The experimental results are encouraging and indicate that the proposed vein uncovering algorithm performs better than the OBVU method and that the uncovered patterns can potentially be used for automatic criminal and victim identification. |
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School of Computer Engineering |
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School of Computer Engineering Zhang, Hengyi Tang, Chaoying Kong, Adams Wai-Kin Craft, Noah |
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Conference or Workshop Item |
author |
Zhang, Hengyi Tang, Chaoying Kong, Adams Wai-Kin Craft, Noah |
author_sort |
Zhang, Hengyi |
title |
Matching vein patterns from color images for forensic investigation |
title_short |
Matching vein patterns from color images for forensic investigation |
title_full |
Matching vein patterns from color images for forensic investigation |
title_fullStr |
Matching vein patterns from color images for forensic investigation |
title_full_unstemmed |
Matching vein patterns from color images for forensic investigation |
title_sort |
matching vein patterns from color images for forensic investigation |
publishDate |
2013 |
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https://hdl.handle.net/10356/83936 http://hdl.handle.net/10220/11981 |
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1681056621077200896 |