Novel Approach For Personal Identification Using Dorsal Knuckle Crease Patterns: A Pilot Study
Published 2024-12-23
Keywords
- Dactyloscopy,
- Anthropometry,
- Minutiae,
- Knuckle crease,
- Proximal interphalangeal
Copyright (c) 2024
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Abstract
Despite the availability of various identification methods, such as fingerprints, ridge density, palm prints, and vein patterns, forensic identification remains a complex challenge. While substantial research has been conducted on the palmar surface of the hand, there has been limited focus on the dorsal surface for identification purposes. The dorsal surface, like fingerprints, contains minutiae and skin crease patterns believed to be permanent. The crease patterns present on the dorsal side of the proximal interphalangeal joints are known as knuckle crease patterns.
This research aimed to classify and examine the characteristics of dorsal finger knuckle crease patterns and to explore their potential for determining sex. A total of 800 finger image samples were collected from 80 subjects. The knuckle crease patterns were categorised into six distinct types: Horizontal, Vertical, Oblique, Semi-lunar, Mixed, and Cross patterns. Additionally, the study investigated sex determination based on the distance between creases, revealing that males tend to have a greater average distance between ridges than females. This difference was statistically confirmed using a t-test with a 95% confidence level.
The findings indicate that finger knuckle crease patterns are unique, individual, and classifiable, making them a valuable tool for identification and potentially aiding forensic investigations.
References
- Acree, M. A. (1999). Is there a gender difference in fingerprint ridge density? Forensic Science International, 102(1), 35–44.
- Badrinath, G.S., Nigam, A., Gupta, P. (2011). An Efficient Finger-knuckle-print based recognition system fusing SIFT and SURF matching scores. Information and communication security ISBN 978-3- -642-25242-6,374-387.
- Bhuvaneshwari, S., Chand, S., Chaudhari, D., Manohar, B., Buyan, L., & Srinivasan, S. (2023). Dactoscopy in human identification: A retrospective study in Bhubaneswar city. Journal of Pharmacy and Bioallied Sciences, 15(Suppl 1), S326–S329. https://doi.org/10.4103/jpbs.jpbs_526_22
- Charles C. (1997). Knuckle profile identity verification system. US Patent 5594806. Google Patent
- Chattopadhyay, S., & Sukul, B. (2012). Identification from dorsal finger pattern: A new approach. Medicine, Science and the Law, 52(1), 17–21.
- Chavan, V., & Kumar, R. (2023). Exploring the potential of ridge density as a measure of sex identification. 11, 2020.
- Gondvikar, S. M., Indurkar, A., Degwekar, S., & Bhowate, R. (2009). Cheiloscopy for sex determination. Journal of Forensic Dental Sciences, 1(2), 56–60.
- Han, C., Cheng, H., Lin, C., & Fan, K. (2003). Personal authentication using palmprint features. Pattern Recognition, 36(2), 371–381.
- Jain, A. K., & Feng, J. (2009). Latent palmprint matching. IEEE Transactions on Pattern Analysis and Machine Intelligence, 31(6), 1032–1047.
- Jain, T., & Kumar, R. (2019). A study of vein recognition system. Acta Informatica Malaysia, 3, 13–15.
- 26480/aim.01.2019.13.15
- John, A. (2021). Comparative study of finger knuckle prints-pilot study. Journal of Forensic Research, 12(9), 4–7.
- Kaushal, N., & Kaushal, P. (2011). Human identification and fingerprints: A review. Journal of Biometrics & Biostatistics, 2(4), Article 123. https://doi.org/10.4172/2155-6180.1000123
- Kennedy, R. A. (1996). Uniqueness of bare feet and its use as a possible means in identification. Forensic Science International, 82(1), 81–87.
- Krishan, K. (2007). Anthropometry in forensic medicine and forensic science: "Forensic anthropometry." Internet Journal of Forensic Sciences, 2(1). DOI:10.5580/1dce
- Kumar, A., & Ravikanth, C. (2009). Personal Authentication Using Finger Knuckle Surface. IEEE Transactions on Information Forensics and Security, 4, 98-110.
- Kumar, A., & Zhou, Y. (2009). Personal identification using finger knuckle orientation features. Electronics Letters, 45, 1023.
- Kumar, A. (2014). Importance of being unique from finger dorsal patterns: Exploring minor finger knuckle patterns in verifying human identities. IEEE Transactions on Information Forensics and Security, 9(8), 1288–1298.
- Limson, K. S., & Julian, R. (2004). Computerized recording of the palatal rugae pattern and an evaluation of its application in forensic identification. Journal of Forensic Odonto-Stomatology, 22(1), 1–4.
- Meijerman, L., Thean, A., & Maat, G. (2005). Earprints in forensic investigations. Forensic Science, Medicine, and Pathology, 1(4), 247–256. https://doi.org/10.1385/FSMP:1:4:247
- Mishra, G., Ranganathan, K., & Saraswathi, T. R. (2009). Study of lip prints. Journal of Forensic Dental Sciences, 1(1), 28–31. https://doi.org/10.4103/0974-2948.50885
- Moore, K.L., Dalley. (2005). Clinical Oriented Anatomy. 5th edn. USA: Lippincott Williams and Wilkins.
- Nandy, A. (2007). Principles of forensic medicine (2nd ed.). Kolkata, India: New Central Book Agency.
- Nanni, L., & Lumini, A. (2009). A multi-matcher system based on knuckle-based features. Neural Computing and Applications, 18, 87-91.
- Nayak, V. C., Rastogi, P., Kanchan, T., Lobo, S. W., Yoganarasimha, K., Nayak, S., Rao, N. G., Kumar, G. P., Shetty, B. S. K., & Menezes, R. G. (2010). Sex differences from fingerprint ridge density in the Indian population. Journal of Forensic and Legal Medicine, 17(2),84–86. https://doi.org/10.1016/j.jflm.2009.09.002
- Sankhyan, D. (2016). Iris patterns as a biometric tool for forensic identifications: A review. Brazilian Journal of Forensic Sciences, Medical Law and Bioethics, 5(2), 205–217.
- Swati, M. R., and Ravishankar, M., (2013). Finger Knuckle Print recognition based on Gabor feature and KPCA+LDA. International Conference on Emerging Trends in Communication, Control, Signal Processing and Computing Applications (C2SPCA), Bangalore, India, 1-5.
- Trabelsi, Selma & Samai, Djamel & Meraoumia, Abdallah & Bensid, Khaled & Benlamoudi, Azeddine & Dornaika, Fadi & taleb-ahmed, Abdelmalik. (2020). Finger-Knuckle-Print Recognition Using Deep Convolutional Neural Network. 163-168. 10.1109/CCSSP49278.2020.9151531.
- Vidhyapriya, R., & S, L. R. (2019). Personal Authentication Mechanism Based on Finger Knuckle Print. Journal of Medical Systems, 43(8), 232.
- Warwick R, Williams P.L. (1973). Gray’s Anatomy. 35th edn. Edinburg: Longman.
- Woodard, D., & Flynn, P.J. (2005). Finger surface as a biometric identifier. Comput. Vis. Image Underst., 100, 357-384.
- Yang, W., Wang, S., Hu, J., Zheng, G., & Valli, C. (2019). Security and accuracy of fingerprint-based biometrics: A review. Symmetry, 11(2),141. https://doi.org/10.3390/sym11020141
- Zhang, L., Zhang, D. (2009). Finger-Knuckle Print: A New Biometric Identifier, Image Processing ICIP, IEEE International Conference, 1981-84.