As it was reviewed in the last article, Hand Geometry Recognition is the oldest Biometric Technology of all. It has its originations going back to the 1960s, and since then, has evolved into a modality which is very reliable, and very rugged to use.

For example, this technology has been known to survive the most brutal and extreme forms of temperature and weather changes, including hurricanes and tsunamis, with the use of the appropriate enclosures.

Hand Geometry Recognition has been predominantly used for Physical Access Entry applications. It is typically used as the primary means of security at the main points of entry into large scale warehouses, factories, storage facilities, etc. It can also be used very well in these scenarios as a Multimodal Security solution, coupled with other non-Biometric technologies, such as Smart Cards.

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The Hand Geometry Recognition device is very bulky, and can impact the end user perception of it. There are also hygiene issues with it, as it requires a direct interface with the hand on the platen to capture the raw images.

However, its primary advantages are that it can contain as many as 40,000 templates of different individuals into one primary database; and that the template size is very small-only 9 Bytes. This allows for very fast Verification Transaction processing, thus requiring very little processing overhead.

However, the hand itself has very little unique features. Only the measurements between the distances of the prominent features of the hand are taken into consideration when compiling the raw images.

The reliability of Hand Geometry Recognition is deemed to be very high, and overall, it has a very strong user acceptance. It is very easy to use and to train the end user on. To a certain extent, it can even take into consideration the physical deformities of a person's hand when confirming his or her identity.

A very close "cousin" to this is the newest Biometric Technology of all: Vein Pattern Recognition.

An Introduction to Vein Pattern Recognition

Vein Pattern Recognition, also known as "VPR" for short, is the latest Biometric Technology to be developed and come out into the marketplace. Since the palm is considered to be just directly underneath the hand, it is also being used as a complement to Hand Geometry Recognition as a Multimodal Security solution.

In fact, Vein Pattern Recognition is giving serious competition to the most traditional modalities, such as that of Fingerprint Recognition and Iris Recognition. It is also considered to be what is known as an "Automated Physical Biometric."

This simply means that Vein Pattern Recognition is a non-contactless type of modality. In other words, there is no direct contact required by the individual to collect the raw images of the veins. Thus, this makes it extremely appealing to the public at large, and potential customers who are interested in using Biometric Technology for security purposes.

In exploring the usage of Vein Pattern Recognition, the question of using veins instead of the arteries often gets asked. There are three primary reasons for this:

1. The veins in the human body are much larger than the arteries;
2. The vein structure is much closer to the surface of the skin, whereas the arteries are located much below the skin surface;
3. Veins carry deoxygenated blood throughout the entire human body. This allows for much more robust images of the vein structure to be captured by the device.

The Science Behind Vein Pattern Recognition

It is the third feature (as listed above) which forms the science behind Vein Pattern Recognition. To fully extract the unique features of the vein pattern (whether it is in the palm or the fingerprint), a Near Infrared (also known as "NIR") light is exposed to the area in question.

The hemoglobin in the blood stream absorbs this NIR light. The hemoglobin is the pigment in the blood stream which is primarily composed of iron, which carries the oxygen in the bloodstream.

The veins contain a much lesser concentration of hemoglobin than what the arteries possess. Because of this, the veins absorb a much higher level of the NIR light.

Thus, the raw images appear much darker and more robust when they are captured by the Vein Recognition device. At this point, the question often gets asked as to how the veins obtain their unique patterns.

Just like the pattern of blood vessels which form the Retina, the unique patterns associated with the veins are created and formed within the first eight weeks of gestation.

The components of Vein Pattern Recognition consist of four main elements, which are as follows:

1. On the device, there is a sensor which consists of a series of Light Emitting Diodes (also known as "LEDs"). These LEDs emit the NIR light to the surface of the palm or fingerprint.
2. A high-resolution Charge-Coupled camera.
3. A separate processing unit which extracts the unique pattern of the blood vessels from either the fingerprint or the palm.
4. The Biometrics database which contains both the Enrollment and the Verification templates. Also, a detailed log history is kept in this database which displays the history of the Verification and/or Identification transactions which have transpired during a pre-established time period.

How Vein Pattern Recognition Works

One of the biggest advantages that a Vein Pattern Recognition devices possess is that it requires no direct contact with the individual. Thus, unlike Hand Geometry Recognition, there are no concerns with hygiene based issues. However, the individual does need to come to a close proximity of the device.

Once this occurs, the NIR light is then shone onto the primary target area, to illuminate the pattern of the vein structures fully. To accomplish this, two separate techniques can be used, and are as follows

1. The Diffused Illumination Technique:

   With this particular method, the NIR light source and the sensor are located together on the same side of the Vein Pattern Recognition device. As a result, the NIR light which is reflected back from either the palm or the fingerprint is then used to capture the raw images of the vein patterns. It should be noted that the thickness of the skin is not an impeding factor here.

2. The Direct Illumination Technique:

   With this approach, the NIR light is flashed straight through the target area on the fingerprint or the palm. This gives the impression of seeing directly through the skin. However, this technique can be greatly affected by the relative thickness of the skin. When a Vein Pattern Recognition device uses this specific approach, the NIR light can be flashed from the top, below, and from the sides of the scanner. There are some advantages and disadvantages with this, depending upon where the NIR light is shone from:

After the raw images are captured, specialized software is then used to crop out any extraneous objects from them. This could include such obstructions as skin hair, or elements which have been captured unknowingly from the external environment.

Case Study: Yarco Company

The Problem

All kinds of business owners face the same administrative nightmares of the human resource function. Many of these headaches stem from having to calculate the total number of hours each employee has worked, and from there, computing the payroll.

However, apart from these issues, herein lies another major flaw: the problem of "Buddy Punching". This occurs when an employee takes an unexcused absence from his or her shift, and has another employee clock in and clock out their hours for them when no work was actually performed.

The Setting

These are the problems which Yarco Company had faced. It is a multifaceted real estate firm, which owns more than 12,000 apartment complexes, across 11 different states. It has a market capitalization of well over $600 million.

Most of the employees still had to manually enter their clock in and clock out times on the traditional time card. Because of this, the payroll department would then have to collect all of these timecards from over 100+ office locations, and then have to enter this into a spreadsheet manually. This process took well over two days to complete.

On top of that, many of these timesheets had to be faxed over to the payroll department, and they were very difficult to read. To make matters even worse, there was no formal review process put into place to have management approve of these timesheets.

As a result, all of the submitted timesheets were assumed to be legitimate no matter what, thus further exacerbating the problem of "Buddy Punching" at Yarco.

The Solution

To eradicate all of these problems outlined, and to cut down on the burgeoning costs of manual payroll processing, Yarco implemented a Vein Pattern Recognition solution. For example, the company installed over 100 Vein Pattern Recognition devices across all divisions of the company. They also configured and implemented a central server that would contain not only all of the Enrollment and Verification Templates but also the clock in and clock out times of each employee.

The Benefits

The benefits of using Vein Pattern Recognition have been immense, and are as follows:

1. A 90% increase in the efficiency rate of payroll processing.
2. The total eradication of having to manually enter the clock in and clock out times of each employee onto a separate spreadsheet.
3. A 50% reduction in the administrative overhead involved with payroll processing.
4. The total elimination of "Buddy Punching".
5. A centralized system was implemented with a web-based software application that allowed the management team to review and formally approve the payroll records quickly and easily.
6. All that is needed on the part of the employee is their unique vein structure; everything else is calculated in real time in just a matter of minutes, as opposed to days under the traditional methods.

Summary and Conclusions

In summary, the advantages and disadvantages of Vein Pattern Recognition can be outlined as follows:

The Advantages

1. The structure of the vein patterns is unique amongst each and every individual. Scientific studies have shown that identical twins possess unique vein patterns as well. With this level of rich data, Vein Pattern Recognition has a very low level of the FRR (False Rejection Rate).
2. The acceptance rate of Vein Pattern Recognition is deemed to be very high.-In fact, it is claimed to be as high as 100%. Much of this can be attributed to the fact that it is a non-contactless modality, which requires very little human intervention. As a result, the issues Civil Liberties and Privacy Rights violations are virtually non-existent.
3. The Verification Transaction processing times is less than one second, and in fact, it is the quickest out of any of the other Biometric modalities. Vein Pattern Recognition is not at all impacted by dirt on the surface of the skin, cuts, bruises, scars, or even moisture or dryness on the fingertips or the palm.
4. Vein Pattern Recognition can be used as a Multimodal Security Solution just by itself. For example, if required, the vein structure on both the fingertip and the palm can be captured and processed by the same device.
5. The processing and storage requirements are very low. Also, the mathematical algorithms used for unique feature extraction and template creation are considered to be very "light," when compared to those used in Iris Recognition and Facial Recognition.
6. It is also very difficult to spoof a Vein Pattern Recognition device because a constant flow of blood is required in the veins for the raw images to be captured.

The Disadvantages

1. Unlike the Iris or the Retina, it is quite possible that the vein pattern structure could change over the lifetime of an individual, thus causing him or her to go through the enrollment process all over again.
2. Vein Pattern Recognition can be greatly affected by the negative effects of the ambient light from the external environment. As a result, this could have a negative impact on the quality of the raw images which are captured.

Finally, Vein Pattern Recognition has also been deemed to be the most versatile Biometric technology of all time. For example, it can be utilized in large scale Physical Access Entry scenarios, and even as a Single Sign-On Solution for Logical Access Entry applications.

In fact, it is even being planned that Vein Pattern Recognition will be used in the 2020 Olympics as one of the primary means in which to confirm the identity of both athletes and spectators, and also as a vehicle into adopting a Virtual Payment infrastructure.

Sources

http://www.biometrics.gov/Documents/vascularpatternrec.pdf

https://arxiv.org/ftp/arxiv/papers/1005/1005.0945.pdf

https://www.arrt.org/pdfs/Examinations/Palm-Vein-Recognition.pdf

https://www.fujitsu.com/us/Images/palmsecure.pdf

https://www.ncsbn.org/NCLEX_Palm_Vein_Recognition_FAQ.pdf

http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.380.388&rep=rep1&type=pdf

http://vbn.aau.dk/files/63418244/CSIP.pdf

http://www.csis.pace.edu/~ctappert/dps/2011IJCB/papers/267.pdf

http://ijssst.info/Vol-15/No-5/data/5198a037.pdf

http://www.irdindia.in/journal_itsi/pdf/vol3_iss5_6/3.pdf

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http://www.hitachi.com/rev/pdf/2015/r2015_05_108.pdf