Overview of the last article
Our previous article dealt with what is deemed to be the ultimate biometric modality of all: retinal recognition.

By itself, the eye is a very powerful organ regarding both uniqueness and richness of data. There is often confusion between the two major parts of the eye, which are the iris and the retina.

The iris is located in the front of the eye, and its primary function is to allow the proper amount of light into the eye structure to facilitate the line of vision.

The retina is located in the back of the eye, and it is a grouping of blood vessels which collects together at a central point, and from there, joins the front of the optic nerve. Its primary purpose is to feed information into it, and from there, it is transmitted to the brain for further processing.

The retina is a very stable component of the eye. It hardly ever changes over the lifetime of the individual, unless he or she is afflicted with some serious ailment, such as that of glaucoma. Since it is inside of the eye, it is also protected from the external environment, thus increasing its stability even more.

The retina possesses many unique features. In fact, scientific studies have shown that it possesses up to 400 unique data points. Also, the enrolment and verification templates which are created are very small in size at only 96 bytes. Thus, this allows for faster verification and/or identification transaction processing to take place.

But, despite all the advantages of retinal recognition, it has suffered from one critical flaw; its user invasiveness. For example, this biometric modality requires a great amount of cooperation from the end-user, at a very close proximity. Because of this, it can be prone to high levels of error, especially in the area of the False Rejection Rate (FRR). Click here to read the full article on the pros and cons of retinal recognition. 

As a result, it has very limited market application usage. It will only be deployed in those areas which require very high levels of security sophistication. Examples of this include nuclear facilities, military installations, and top-secret research and development facilities. As such, it is expected that retinal recognition will not grow any more regarding market applications.

Introduction to hand geometry recognition
On the other end of the spectrum of the biometric modalities, is that of hand geometry recognition. In fact, it can be entitled as the “oldest biometric technology of all”, because it even predates the evolution of fingerprint recognition.

The birth of hand geometry recognition goes back all the way to the 1960s.

It was patented in 1985, and by the early 1990s, it started to take heavy market dominance.

At present, unlike the other biometric modalities, there is only one primary vendor which develops this particular technology.

Also, in sharp contrast to the retina, the hand itself does not really possess any unique data points.

Rather, its distinctiveness comes from its shape. For this very reason, hand geometry recognition is not really used in identification types of scenarios, where numerous data points are required.

It is used primarily for verification-based applications, such as those of physical access entry and time/attendance.

But, one of the key advantages of hand geometry recognition is that it can be used in some of the harshest and most punishing environments imaginable.

For example, it can be used in warehouses, storage facilities, and factories, where the population sizes are very large. In fact, a single device can store over 40,000 biometric templates of different individuals.

Hand geometry recognition can also be used in the most extreme of heat and cold, and has even been known to withstand such forces of nature as hurricanes and tsunamis.

The distinctiveness of the hand falls into seven categories:

  • The overall shape of the hand;
  • The various dimensions of the palm;
  • The length and width of all ten fingers;
  • The various measurements between the distances of the joints of the hand;
  • The various shapes of the knuckles;
  • The geometrical circumference of the fingers;
  • Any distinct landmark features that can be found on the hand.

Part 2 will examine how the biometric templates are created; as well as the advantages and the disadvantages of hand geometry recognition.

Keesing Technologies

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The global market leader in banknote and ID document verification

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Ravi Das is a Cybersecurity Consultant and Business Development Specialist. He also does Cybersecurity Consulting through his private practice, RaviDas Tech, Inc. He also possesses the Certified in Cybersecurity (CC) cert from the ISC2.
Visit his website at mltechnologies.io

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