Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
10.1145/3577163.3595096acmconferencesArticle/Chapter ViewAbstractPublication Pagesih-n-mmsecConference Proceedingsconference-collections
research-article
Open access

On the Feasibility of Post-Mortem Hand-Based Vascular Biometric Recognition

Published: 28 June 2023 Publication History

Abstract

Recently, there is a growing interest to employ biometrics in post-mortem forensics, mainly to replace cost intensive radiology based imaging devices. While it has been shown that post-mortem biometric recognition is feasible for fingerprints, face and iris, no studies regarding post-mortem vasculature pattern recognition have been published. Based on the first reported post-mortem hand- and finger-vein dataset, the hypothesis, that hand vasculature biometrics can be used as post-mortem biometric modality, is falsified. Using an indirect proof, it is shown that no usable vascular features are present in the small amount of sample data collected, by visual inspection as well as by applying several biometric quality metrics, which confirm that hand-based vasculature biometrics can not be used as post-mortem biometric modality.

References

[1]
M. S. M. Asaari, S. A. Suandi, and B. A. Rosdi. 2014. Fusion of Band Limited Phase Only Correlation and Width Centroid Contour Distance for finger based biometrics. Expert Systems with Applications, Vol. 41, 7 (2014), 3367--3382.
[2]
Samarth Bharadwaj, Mayank Vatsa, and Richa Singh. 2014. Biometric quality: a review of fingerprint, iris, and face. EURASIP Journal on Image and Video Processing, Vol. 2014 (2014), 34. https://doi.org/10.1186/1687-5281-2014-34
[3]
David S Bolme, Ryan A Tokola, Chris B Boehnen, Tiffany B Saul, Kelly A Sauerwein, and Dawnie Wolfe Steadman. 2016. Impact of environmental factors on biometric matching during human decomposition. In 2016 IEEE 8th International Conference on Biometrics Theory, Applications and Systems (BTAS). IEEE, 1--8.
[4]
Aidan Boyd, Shivangi Yadav, Thomas Swearingen, Andrey Kuehlkamp, Mateusz Trokielewicz, Eric Benjamin, Piotr Maciejewicz, Dennis Chute, Arun Ross, Patrick Flynn, et al. 2020. Post-mortem iris recognition-a survey and assessment of the state of the art. IEEE Access, Vol. 8 (2020), 136570-136593.
[5]
David C Cornett, David S Bolme, Dawnie W Steadman, Kelly A Sauerwein, and Tiffany B Saul. 2019. Effects of postmortem decomposition on face recognition. In 2019 IEEE 10th International Conference on Biometrics Theory, Applications and Systems (BTAS). IEEE, 1--8.
[6]
Luca Debiasi, Christof Kauba, Bernhard Prommegger, and Andreas Uhl. 2018. Near-Infrared Illumination Add-On for Mobile Hand-Vein Acquisition. In 2018 IEEE 9th International Conference on Biometrics Theory, Applications and Systems (BTAS) (October 22 - October 25). Los Angeles, California, USA, 1--9. https://doi.org/10.1109/BTAS.2018.8698575
[7]
Laura Carolina Martínez Esmeral and Andreas Uhl. 2022a. Low-effort re-identification techniques based on medical imagery threaten patient privacy. In Medical Image Understanding and Analysis: 26th Annual Conference, MIUA 2022, Cambridge, UK, July 27-29, 2022, Proceedings. Springer, 719--733.
[8]
Laura Carolina Martínez Esmeral and Andreas Uhl. 2022b. Patient identification methods based on medical imagery and their impact on patient privacy and open medical data. In 2022 IEEE 35th International Symposium on Computer-Based Medical Systems (CBMS). IEEE, 406--411.
[9]
Silke Grabherr, Coraline Egger, Raquel Vilarino, Lorenzo Campana, Melissa Jotterand, and Fabrice Dedouit. 2017. Modern post-mortem imaging: an update on recent developments. Forensic sciences research, Vol. 2, 2 (2017), 52--64.
[10]
Patrick Grother and Elham Tabassi. 2007. Performance of Biometric Quality Measures. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 29, 4 (2007), 531--543. https://doi.org/10.1109/TPAMI.2007.1019
[11]
Rafał Kabaciński and Mateusz Kowalski. 2011. Vein pattern database and benchmark results. Electronics Letters, Vol. 47, 20 (2011), 1127--1128. https://doi.org/10.1049/el.2011.1441
[12]
Christof Kauba, Bernhard Prommegger, and Andreas Uhl. 2018. The Two Sides of the Finger - An Evaluation on the Recognition Performance of Dorsal vs. Palmar Finger-Veins. In Proceedings of the International Conference of the Biometrics Special Interest Group (BIOSIG) (September 27-28). Darmstadt, Germany.
[13]
Christof Kauba and Andreas Uhl. 2018. Shedding Light on the Veins - Reflected Light or Transillumination in Hand-Vein Recognition. In Proceedings of the 11th IAPR/IEEE International Conference on Biometrics (ICB'18) (Feb 20 - Feb 23). Gold Coast, Queensland, Australia, 1--8. https://doi.org/10.1109/ICB2018.2018.00050
[14]
Simon Kirchgasser, Christof Kauba, Georg Wimmer, and Andreas Uhl. 2023. Advanced Image Quality Assessment for Hand- and Fingervein Biometrics. https://doi.org/10.48550/ARXIV.2302.09973
[15]
Ajay Kumar and Yingbo Zhou. 2012. Human identification using finger images. IEEE Transactions on Image Processing, Vol. 21, 4 (2012), 2228--2244.
[16]
Patrick J Laberke, Garyfalia Ampanozi, Thomas D Ruder, Dominic Gascho, Michael J Thali, and Juergen Fornaro. 2017. Fast three-dimensional whole-body post-mortem magnetic resonance angiography. Journal of Forensic Radiology and Imaging, Vol. 10 (2017), 41--46.
[17]
Yu Lu, Shan Juan Xie, Sook Yoon, Zhihui Wang, and Dong Sun Park. 2013. An available database for the research of finger vein recognition. In 6th International Congress on Image and Signal Processing (CISP), Vol. 1. 410--415.
[18]
Kresimir Matkovic, László Neumann, Attila Neumann, Thomas Psik, Werner Purgathofer, et al. 2005. Global contrast factor-a new approach to image contrast. In CAe. 159--167.
[19]
Anish Mittal, Anush Krishna Moorthy, and Alan Conrad Bovik. 2012a. No-Reference Image Quality Assessment in the Spatial Domain. IEEE Transactions on Image Processing, Vol. 21, 12 (2012), 4695--4708.
[20]
Anish Mittal, Rajiv Soundararajan, and Alan C. Bovik. 2012b. Making image quality assessment robust. In Proceesings of the 46th Asilomar Conference on Signals, Systems and Computers (ASILOMAR).
[21]
Dat Nguyen, Y.H. Park, K.Y. Shin, and K.R. Park. 2013. New finger-vein recognition method based on image quality assessment. KSII Transactions on Internet and Information Systems, Vol. 7, 2 (2013), 347--365. https://doi.org/10.3837/tiis.2013.02.010
[22]
Curtis E Offiah and Jonathan Dean. 2016. Post-mortem CT and MRI: appropriate post-mortem imaging appearances and changes related to cardiopulmonary resuscitation. The British journal of radiology, Vol. 89, 1058 (2016), 20150851.
[23]
Karen Panetta, Srijith Rajeev, KM Shreyas Kamath, and Sos S Agaian. 2019. Unrolling post-mortem 3D fingerprints using mosaicking pressure simulation technique. Ieee Access, Vol. 7 (2019), 88174--88185.
[24]
Huafeng Qin and Mounîm A. El-Yacoubi. 2015. Finger-Vein Quality Assessment by Representation Learning from Binary Images. In Neural Information Processing, Sabri Arik, Tingwen Huang, Weng Kin Lai, and Qingshan Liu (Eds.). Springer International Publishing, Cham, 421--431.
[25]
Huafeng Quin and Mounim A. El-Yacoubi. 2019. Finger-Vein Quality Assessment Based on Deep Features From Grayscale and Binary Images. International Journal of Pattern Recognition and Artificial Intelligence, Vol. 33, 11 (2019), 1940022.
[26]
Srijith Rajeev, Shreyas Kamath KM, and Sos S Agaian. 2016. Method for modeling post-mortem biometric 3D fingerprints. In Mobile Multimedia/Image Processing, Security, and Applications 2016, Vol. 9869. SPIE, 159--168.
[27]
Oliver Remy, Jutta Hämmerle-Uhl, and Andreas Uhl. 2022. Fingervein Sample Image Quality Assessment using Natural Scene Statistics. In 2022 International Conference of the Biometrics Special Interest Group (BIOSIG'22). 1--6. https://doi.org/10.1109/BIOSIG55365.2022.9896974
[28]
Hengyi Ren, Lijuan Sun, Jian Guo, Chong Han, and Ying Cao. 2022. A high compatibility finger vein image quality assessment system based on deep learning. Expert Systems with Applications, Vol. 196 (2022), 116603. https://doi.org/10.1016/j.eswa.2022.116603
[29]
Alora Sansola. 2015. Postmortem iris recognition and its application in human identification. ProQuest Dissertations and Theses, Vol. 70 (2015).
[30]
Kelly Sauerwein, Tiffany B Saul, Dawnie Wolfe Steadman, and Chris B Boehnen. 2017. The effect of decomposition on the efficacy of biometrics for positive identification. Journal of forensic sciences, Vol. 62, 6 (2017), 1599--1602.
[31]
Ana F. Sequeira, James Ferryman, Lulu Chen, Chiara Galdi, Jean-Luc Dugelay, Valeria Chiesa, Andreas Uhl, Bernhard Prommegger, Christof Kauba, Simon Kirchgasser, Artur Grudzien, Marcin Kowalski, Lukasz Szklarski, Patryk Maik, and Piotr Gmitrowicz. 2018. PROTECT Multimodal DB: a multimodal biometrics dataset envisaging Border Control. In Proceedings of the International Conference of the Biometrics Special Interest Group (BIOSIG'18) (September 27-28). Darmstadt, Germany, 1--8. https://doi.org/10.23919/BIOSIG.2018.8552926
[32]
Pedro Tome and Sébastien Marcel. 2015. On the vulnerability of palm vein recognition to spoofing attacks. In 2015 International Conference on Biometrics (ICB). IEEE, 319--325.
[33]
B.T. Ton and R.N.J. Veldhuis. 2013. A high quality finger vascular pattern dataset collected using a custom designed capturing device. In International Conference on Biometrics, ICB 2013. IEEE. http://doc.utwente.nl/87790/
[34]
Mateusz Trokielewicz, Adam Czajka, and Piotr Maciejewicz. 2016. Post-mortem human iris recognition. In 2016 International Conference on Biometrics (ICB). IEEE, 1--6.
[35]
Mateusz Trokielewicz, Adam Czajka, and Piotr Maciejewicz. 2020. Post-mortem iris recognition with deep-learning-based image segmentation. Image and Vision Computing, Vol. 94 (2020), 103866.
[36]
Andreas Uhl. 2019. State of the Art in Vascular Biometrics. In Handbook of Vascular Biometrics, Andreas Uhl, Christoph Busch, Sebastien Marcel, and Raymond Veldhuis (Eds.). Springer Nature Switzerland AG, Cham, Switzerland, Chapter 1, 3--61. https://doi.org/10.1007/978-3-030-27731-4
[37]
C. Wang, X. Zeng, X. Sun, W. Dong, and Z. Zhu. 2017. Quality assessment on near infrared palm vein image. In 2017 32nd Youth Academic Annual Conference of Chinese Association of Automation (YAC). 1127--1130. https://doi.org/10.1109/YAC.2017.7967580
[38]
Lu Yang, Gongping Yang, Yilong Yin, and Rongyang Xiao. 2013. Finger vein image quality evaluation using support vector machines. Optical Engineering, Vol. 52 (2013), 10--52. https://doi.org/10.1117/1.OE.52.2.027003
[39]
Yilong Yin, Lili Liu, and Xiwei Sun. 2011. SDUMLA-HMT: a multimodal biometric database. In Chinese Conference on Biometric Recognition. Springer, 260--268.
[40]
Junying Zeng, Yao Chen, and Chuanbo Qin. 2018. Finger-vein Image Quality Assessment Based on light-CNN. In Proceedings of the 14th IEEE International Conference on Signal Processing (ICSP'18). 768--773. io

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
IH&MMSec '23: Proceedings of the 2023 ACM Workshop on Information Hiding and Multimedia Security
June 2023
190 pages
ISBN:9798400700545
DOI:10.1145/3577163
This work is licensed under a Creative Commons Attribution International 4.0 License.

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 June 2023

Check for updates

Author Tags

  1. biometric quality evaluation
  2. finger-vein recognition
  3. hand-vein recognition
  4. post-mortem biometrics
  5. vascular pattern recognition

Qualifiers

  • Research-article

Funding Sources

Conference

IH&MMSec '23
Sponsor:

Acceptance Rates

Overall Acceptance Rate 128 of 318 submissions, 40%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 184
    Total Downloads
  • Downloads (Last 12 months)124
  • Downloads (Last 6 weeks)9
Reflects downloads up to 01 Nov 2024

Other Metrics

Citations

View Options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Get Access

Login options

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media