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Biometric Comparison Table

Below is a summary of the main issues and requirements of biometric technologies as well as a table comparing the issues:

  1. Accuracy – Field tests have shown that state-of-the-art biometric technologies are still providing only 99% accuracy. This means a failure 1 out of 100 times, which is unacceptable for a wide variety of applications such as:  identity verification for credit cards; keyless access to home, office, & automobile; government security; fast track border crossing lanes; ATM banking; and identity theft prevention among others.
  2. Size – The vast majority of applications require a very small verification device taking up very little space.  These include point-of-sale systems, keyless access to automobile, ATM systems, and others.
  3. Speed – Verification must be done extremely quickly.  Even 10 seconds is too long for most applications.
  4. Cost – High cost for verification creates too much overhead for most applications.
  5. Privacy concerns – A sizable percentage (about 20%) of the population is not in favor of having private biological information being stored in a database.  The resistance of this small percentage of the population is an obstacle to universal and widespread adoption of biometrics technologies in many markets.
  6. Consumer convenience – In addition, there is resistance to ‘privacy-invasive’ procedures, such as a laser scan of the retina.  Ideal convenience means the consumer undergoes a very carefree process, which is quickly completed with no psychological or physical discomfort.
  7. Robust reliability – A device must function robustly in all manner of conditions: heat, cold, humidity, pink-eye, sweaty hands, dirty hands, etc.
  8. Identity theft deterrence – The most successful technology will be the one that makes it very hard, close to impossible, to steal someone else's identity.  

IDesia's Biometric Technologies Comparison Table

The comparison of biometric technologies is not based on mathematically measurable variables. Some parameters are subjective and some are context dependent, such as usability and privacy.

Publicized comparison tables do not specify under what conditions the different variables were measured, so that different tables show different results.

In our table, we have tried to use the different technologies' vendors published results of their own laboratory trials while subjective parameters comparison is based on 'common knowledge' and information from other such tables.

The legend to our table reads as follows:

Excellent
Excellent
Good
Good
Fair
Fair
Poor Poor

 

IDesia's Biometric Technologies Comparison Accuracy Usability Smallness Spoof Proof Speed Privacy Low Cost Universality
IDesia BDS

Good

Good

Excellent

Excellent

Good

Good

Excellent

Good

Fingerprint

Fair

Fair

Fair

Poor

Good

Good

Fair

Iris Recognition

Excellent

Poor

Poor

Good

Fair

Good

Poor

Good

Hand Scan

Fair

Fair

Poor

Poor

Fair

Excellent

Fair

Excellent

Vein Scan

Fair

Fair

Fair

Good

Fair

Excellent

Fair

Fair

Facial Scan

Poor

Fair

Fair

Fair

Fair

Excellent

Fair

Excellent

Signature Recognition

Poor

Good

Good

Fair

Good

Excellent

Good

Good

Voice Recognition

Poor

Good

Good

Fair

Fair

Excellent

Good

Excellent

 

Definitions

Accuracy  Indicates how accurately the technology measures the individual’s identification
Usability Indicates ease of use of the system
Smallness Indicates the size of the capturing device
Spoof Proof Indicates how easy it is to fool the system and impersonate someone else
Speed Indicates the length of time from beginning of operation until final authentication/identification
Privacy Indicates the degree to which the system is perceived as intruding into the person’s privacy
Low Cost Indicates total cost of the system and its implementation
Universality Indicates the degree to which the specific trait being measured is present in everyone