A systematic review of iris biometrics in forensic science: applications and challenges

被引:0
作者
Bhatt, Sushil [1 ,2 ]
Sehrawat, Jagmahender Singh [1 ]
Gupta, Vishali [2 ]
机构
[1] Panjab Univ, Dept Anthropol, Chandigarh, India
[2] PGIMER, Adv Eye Ctr, Chandigarh, India
关键词
Forensic; Biometrics; Cataract; Iris biometrics; IAAD; Cadaver;
D O I
10.1186/s41935-025-00431-7
中图分类号
DF [法律]; D9 [法律]; R [医药、卫生];
学科分类号
0301 ; 10 ;
摘要
BackgroundIn today's digital era, traditional security methods like passwords and logins have become increasingly vulnerable to hacking and inefficiency. As a more secure alternative, iris biometrics, often referred to as a "living password," offer enhanced security due to the iris's unique and complex patterns. This review explores the challenges and advancements in iris biometric technology, focusing on its application in postmortem identification.Main bodyUsing a Boolean search methodology, relevant studies were identified from databases such as Embase, PubMed, Web of Science, and Scopus. Out of 281 articles retrieved, only 17 met the inclusion criteria for this review. The selected studies cover critical topics, including iris de-identification, postmortem iris recognition, the impact of ocular diseases on iris biometrics, and the decomposition of the iris after death. The review also highlights significant advancements in iris recognition algorithms and imaging technologies, particularly the use of near-infrared (NIR) imaging, which has proven effective in identifying cadaver eyes. Despite these advancements, challenges such as iris spoofing and the effects of disease and decomposition on iris identification remain key concerns.ConclusionThe findings emphasize the need to integrate advanced biometric techniques into forensic science to protect biometric evidence and ensure secure identification in both digital and forensic applications. This review highlights the importance of ongoing innovation in biometric technologies to address the evolving challenges posed by digital security and forensic integrity.
引用
收藏
页数:7
相关论文
共 18 条
  • [1] Iris Deidentification With High Visual Realism for Privacy Protection on Websites and Social Networks
    Barni, Mauro
    Labati, Ruggero Donida
    Genovese, Angelo
    Piuri, Vincenzo
    Scotti, Fabio
    [J]. IEEE ACCESS, 2021, 9 : 131995 - 132010
  • [2] Post-Mortem Iris Recognition-A Survey and Assessment of the State of the Art
    Boyd, Aidan
    Yadav, Shivangi
    Swearingen, Thomas
    Kuehlkamp, Andrey
    Trokielewicz, Mateusz
    Benjamin, Eric
    Maciejewicz, Piotr
    Chute, Dennis
    Ross, Arun
    Flynn, Patrick
    Bowyer, Kevin
    Czajka, Adam
    [J]. IEEE ACCESS, 2020, 8 : 136570 - 136593
  • [3] Statistical richness of visual phase information: Update on recognizing persons by iris patterns
    Daugman, J
    [J]. INTERNATIONAL JOURNAL OF COMPUTER VISION, 2001, 45 (01) : 25 - 38
  • [4] Daugman J, 2009, ESSENTIAL GUIDE TO IMAGE PROCESSING, 2ND EDITION, P715, DOI 10.1016/B978-0-12-374457-9.00025-1
  • [5] Devireddy SK, 2009, Computer Science & Telecommunications, V2009
  • [6] Iris pigmentation as a quantitative trait: variation in populations of European, East Asian and South Asian ancestry and association with candidate gene polymorphisms
    Edwards, Melissa
    Cha, David
    Krithika, S.
    Johnson, Monique
    Cook, Gillian
    Parra, Esteban J.
    [J]. PIGMENT CELL & MELANOMA RESEARCH, 2016, 29 (02) : 141 - 162
  • [7] Garg M, 2016, Journal of Control Theory and Applications, V2016
  • [8] The color of the human eye: A review of morphologic correlates and of some conditions that affect iridial pigmentation
    Imesch, PD
    Wallow, IHL
    Albert, DM
    [J]. SURVEY OF OPHTHALMOLOGY, 1997, 41 : S117 - S123
  • [9] Iris Liveness Detection for Biometric Authentication: A Systematic Literature Review and Future Directions
    Khade, Smita
    Ahirrao, Swati
    Phansalkar, Shraddha
    Kotecha, Ketan
    Gite, Shilpa
    Thepade, Sudeep D.
    [J]. INVENTIONS, 2021, 6 (04)
  • [10] Long range iris recognition: A survey
    Nguyen, Kien
    Fookes, Clinton
    Jillela, Raghavender
    Sridharan, Sridha
    Ross, Arun
    [J]. PATTERN RECOGNITION, 2017, 72 : 123 - 143