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It should be noted that the hand itself does not possess any unique features per se, but rather, it is the shape of the hand (or the geometry of the hand) which is unique amongst most individuals. Given this situation, hand geometry recognition rarely used for large scale identification purposes. Rather, it is used for verification purposes only.

And in his regard, it can serve very large scale applications for very harsh environments, such as physical access entry for warehouses, storage facilities, and factories. It is also used widely in time and attendance scenarios as well. In these verification scenarios, very often a smart card is also used, which is used to store further encrypted data about the end user.

In the enrollment process, some 96+ measurements of the hand are taken, and this includes the following variables:

  1. The overall shape of the hand;
  2. The various dimensions of the palm;
  3. The length and width of all ten fingers;
  4. The measurement between the distances of the joints of the hand;
  5. The various shapes of the knuckles;
  6. The geometrical circumference of the fingers;
  7. Any distinct landmark features which can be found on the hand.

Hand Geometry Recognition-The Enrollment Process

To start the enrollment process with a hand geometry scanner, a combination of prisms and Light Emitting Diodes (LEDs) from within the scanner are used, to help capture the raw images of the hand. The technology can capture images of the back of the hand as well as the palm. This creates a 2- Dimensional image of the hand.

In order to capture a 3-Dimensional image of the hand, five pegs guiding pegs are located just underneath the camera, to help the end user position their hand properly. Although this is advantageous, this method also possesses on serious disadvantage. For instance, the images of these pegs are also captured into the raw image. This results in greatly increased processing time because the images of the pegs have to be removed.

Also, because of this, the extraction algorithm cannot take into account for variances due to hand rotation and differences in the placement of the hand. To create the enrollment template, the average of the measurements described previously are calculated, which is then converted into binary mathematical file. This is very small, only nine bytes.

A problem in the construction of the enrollment and verification templates is that the geometric features of the hand share quite a bit of resemblance or correlation with another, which can greatly hinder the process of unique feature extraction. To help alleviate this problem, a method known as Principal Component Analysis, or PCA, is used to produce a set of geometric features which are uncorrelated, and thus unique features can be extracted.

The small biometric template size of hand geometry scanning gives it a rather distinct advantage. For example, hand geometry recognition works very effectively and is very interoperable as a multimodal security solution for both physical and logical access entry, as well as for time and attendance applications. As a stand alone device, a hand geometry recognition device can store upwards of 40,000+ unique biometric templates.

Hand Geometry Recognition-The Advantages & Disadvantages

As reviewed in the strengths and weaknesses of fingerprint recognition, the same seven criterion can be used to review the advantages and disadvantages of hand geometry recognition as well:

  1. Universality: When compared to other biometric technologies on a spectrum, hand geometry recognition does very well here. This is so because most end users have at least one hand which they can use in order to be verified. The technology has advanced to the point that it can take into account, up to a certain degree, any deformities of the hand. Also, hand geometry recognition is not affected at all by any type or kind of skin color-it is the just the shape of the hand which is captured. Also, the technology is very easy to use and train individuals on. For example, at most, an end user needs to know how to place their hand properly onto the platen, and how to swipe a smart card;
  2. Uniqueness: Although each individual does possess a different hand shape, the unique features which are extracted do not possess the very rich information and data like the iris and retina possess;
  3. Permanence: Although the dimensions of the hand are relatively stable throughout the lifetime of an individual, the hand is very susceptible to physical changes. This includes such factors as weight loss and weight gain, injuries, as well as various diseases;
  4. Collectability: This is another key advantage for hand geometry recognition. Except for the variables just described in #3, the raw images of the hand which are captured are not affected at all to things which could affect the surface of the skin, and this includes primarily grime, dirt, and scars. Thus, this key strength makes hand geometry recognition very suitable for very harsh and extreme weather environments;
  5. Performance: Overall, hand geometry scanners are very easy to use, and it’s very small template size (only 9 bytes) makes this technology very interoperable with other types and kinds of security systems. Also, the accuracy rate of hand geometry recognition is very high, ranked with an Equal Error Rate (ERR) of 0.1% (see Chapter 1 for a detailed explanation of the ERR, as well as other important performance metrics). But, hand geometry scanners are large and bulky, and this can prove to be a very serious disadvantage;
  6. Acceptability: For the most part, hand geometry recognition is well received by the end user population, and is perceived to be very non-invasive. The only major in this aspect is the hygiene of the hand geometry scanner, such as any germs or contaminants left behind by other users;
  7. Resistance to circumvention: Just because a hand geometry scanner is very easy to use, on the contrary, it is very difficult to spoof. Trying to fool this kind of system would mean creating an entire 3-Dimensional hand, using a false, physical mock-up of it.

As mentioned, hand geometry recognition is used primarily for physical access entry and time/attendance applications. But, it has also made its way at the international airport setting, used primarily in the United States Citizenship and Immigration Service Passenger Accelerated System, or also known as INSPASS.

This program has been designed so that frequent flyer passengers, especially those of business travelers, can be enrolled into what is known as a “trusted travel program”. With this, a passenger can enter into the country of their destination with a mere scan of their hand, rather than wasting time at customs and immigration lines using the traditional paper passport. Currently, this program is in use in the United States, Canada, and Israel.