Geometry of a hand and some examples of measurements that can be taken by hand geometry reading devices.[1]
A hand geometry reading device with pegs to control the placement of the hand. Angled mirror on the left reflects the side view image of the hand to the camera. A CCD camera is beneath the keypad to take the top view image of the hand and the mirror image.[2]

Hand geometry is a biometric that identifies users from the shape of their hands. Hand geometry readers measure a user's palm and fingers along many dimensions including length, width, deviation, and angle and compare those measurements to measurements stored in a file.[3]

History

Viable hand geometry devices have been manufactured since the early 1970s, making hand geometry the first biometric to find widespread computerized use.[4] Robert Miller realized the distinctive features of hand sizes and shapes could be used for identification and patented the first automated hand geometry device at the Stanford Research Institute in 1971. The device would measure the hand, and the numbers needed to match the punched holes of a user ID card to activate the circuit to be identified. David Sidlauskas was also a major player in the hand geometry device production, and he patented Handkey ID3D, the first hand scanner that worked in 3D that involved an optical measuring plate, camera, and numeric keypad to enter a personal PIN.[5]

As an add-on

Hand geometry is not thought to be as unique as fingerprints, palm veins or irises. Fingerprinting and iris recognition remain the preferred technology for high-security applications. In large populations, hand geometry is not suitable for so-called one-to-many applications, in which a user is identified from his biometric without any other identification. However, hand geometry is very reliable when combined with other forms of identification, such as identification cards or personal identification numbers. There have also been proposed methods to include hand-geometry with palm print-based verification for better accuracy and performance.[6]

Commercial use

There have been many patents issued for devices that measure hand geometry from the U.S. patent office.[7]

A hand-geometry system‚ Identimat, was used at Shearson Hamil on Wall Street to track attendance, marking the beginning of biometric technology usage.[8][9] Based on Robert Miller's patent, Identimat utilized light sensing cells to measure finger length and a magnetic strip card reader to verify identification cards and compared the information given to determine the authorization of the person. Although production ceased in 1987, the idea remains popular; common applications include access control and time-and-attendance operations.[10]

Advantages

Although hand geometry is not considered to be the most secure compared to other biometric points, there are some advantages to this method. This includes:[3]

  • Medium cost
  • Fast results due to low-computational cost algorithms
  • Reduced template size so takes up less storage
  • Easy to use

Disadvantages

Although the performance of these systems is not shown to be influenced by factors such as dry skin, large rings and swelling in the fingers may pose problems.

They are not universally accessible, as they cannot be used by those with paralysis or Parkinson's disease, and they can be deceived using high-quality bone structure models.[11]

Pay-by-hand

Hand-recognition payment, also named pay-by-hand is a payment method that uses the scanning of one's hand.[12] It is an alternative payment system to using credit cards. The technology uses biometric identification by scanning the client's hand and reading various features like the position of veins and bones and it was tested by Amazon since 2019.[13]

See also

References

  1. ↑ "Hand Geometry" (PDF). National Science and Technology Council (US). 7 August 2006. Retrieved 28 November 2013.
  2. ↑ Bača, Miroslav; Grd, Petra; Fotak, Tomislav (2012). "Basic Principles and Trends in Hand Geometry and Hand Shape Biometrics". New Trends and Developments in Biometrics. doi:10.5772/51912. ISBN 978-953-51-0859-7. S2CID 35307022.
  3. 1 2 Sanchez-Reillo, R.; Sanchez-Avila, C.; Gonzalez-Marcos, A. (October 2000). "Biometric identification through hand geometry measurements". IEEE Transactions on Pattern Analysis and Machine Intelligence. 22 (10): 1168–1171. doi:10.1109/34.879796.
  4. ↑ Mayhew, Stephen (2012-06-22). "Explainer: Hand Geometry Recognition | Biometric Update". www.biometricupdate.com. Retrieved 2021-05-24.
  5. ↑ Prihodova, Katerina; Hub, Miloslav (June 2019). Biometric Privacy through Hand Geometry- A Survey. 2019 International Conference on Information and Digital Technologies. pp. 395–401. doi:10.1109/DT.2019.8813660. ISBN 978-1-7281-1401-9. S2CID 201811120.
  6. ↑ Kumar, Ajay; Wong, David C.M.; Shen, Helen C.; Jain, Anil K. (October 2006). "Personal authentication using hand images". Pattern Recognition Letters. 27 (13): 1478–1486. Bibcode:2006PaReL..27.1478K. doi:10.1016/j.patrec.2006.02.021.
  7. ↑ Kumar, Ajay; Wong, David C. M.; Shen, Helen C.; Jain, Anil K. (2003), "Personal Verification Using Palmprint and Hand Geometry Biometric", Audio- and Video-Based Biometric Person Authentication, Lecture Notes in Computer Science, vol. 2688, Berlin, Heidelberg: Springer Berlin Heidelberg, pp. 668–678, doi:10.1007/3-540-44887-x_78, ISBN 978-3-540-40302-9, retrieved 2021-11-05
  8. ↑ Kumar, Ajay; Zhang, David (June 2007). "Hand-Geometry Recognition Using Entropy-Based Discretization". IEEE Transactions on Information Forensics and Security. 2 (2): 181–187. doi:10.1109/tifs.2007.896915. hdl:10397/222. S2CID 3175836.
  9. ↑ "Introduction". Palmprint Authentication. International Series on Biometrics. Vol. 3. 2004. pp. 3–19. doi:10.1007/1-4020-8097-2_1. ISBN 1-4020-8096-4.
  10. ↑ Prihodova, Katerina; Hub, Miloslav (2019). "Biometric Privacy through Hand Geometry- A Survey". 2019 International Conference on Information and Digital Technologies (IDT). pp. 395–401. doi:10.1109/dt.2019.8813660. ISBN 978-1-7281-1401-9. S2CID 201811120.
  11. ↑ Varchol, P., Levický, D., Sk, P., Levicky@tuke, D., & Sk. (n.d.). Using of Hand Geometry in Biometric Security Systems. Retrieved March 9, 2023, from https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=f007fec363d2e2cba1cd96fe556ab2d4674201e8
  12. ↑ Grothaus, Michael (20 January 2020). "Amazon wants you to use your hand to pay for things at third-party retailers". Fast Company.
  13. ↑ Levy, Nat (20 January 2020). "Here's how Amazon's rumored pay-by-hand tech could work". GeekWire.

References

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