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Factors that Help in Selecting the Best Biometric Device

Published on 24 July 15
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There was a time when the choices related to purchasing a biometric device were limited and many desired features were either absent or extremely expensive for most of the commercial purposes. Hence, the implementation of biometrics to enhance security was limited to government agencies and national projects. However, in recent years the biometric industry has developed by leaps & bounds and has immensely improved its manufacturing & technological capabilities. The much needed ramifications of these changes are reduced cost and better integration with the other enterprise level systems that made biometric industry a multi-billion dollar industry in virtually no time.


Some factors that are helpful in purchasing the right biometric device are briefly discussed below.



Quality of Extracted Image


The process of biometric identification starts with the extraction of a biometric identifier such as fingerprints, iris patterns, veins, etc. with the help of a scanner. This extracted image of the identifier is then converted into digital templates using various techniques (vary from manufacturer to manufacturer) and consequently stored in a database for future matching. If the quality of the extracted image (and therefore of digital templates thus formed) is poor or not up to the minimal DPI (Dots Per Inch) required, then the matching process in most cases would lead to high FRR (False Rejection Rate). In case of fingerprint readers, there are many certifications such as FBI IAFIS IQS Appendix F & PIV-071006, WSQ, etc. that ensure the quality of reader is up to the standards required.



Processing Speed


The most significant feature of any biometric system (or any other security system) is its accuracy in determining who should get access to a facility and who doesn't. In addition to this, it's also important that these systems are capable of enrolling and matching biometric identifiers at an acceptable processing speed without compromising the accuracy of the process in any way whatsoever. This feature becomes even more important in big facilities where a large number of employees are enrolled and hundreds of matches happen every hour.


FAR & FRR


These two terms are critical when you are comparing two biometric devices. Let's understand their importance by taking the example of a fingerprint reader. During matching when the current template is matched with an existing template (in the database) of the same person, it's known as genuine matching and when compared with other templates, it's known as impostor matching. Ideally, genuine scores should be 100 % and impostor scores should be zero percent. In false acceptance rate (FAR), impostor scores are high enough that the matching algorithm takes them as genuine and allows access. Whereas, in false rejection rate (FRR), genuine scores are not high enough and are treated as impostor scores so that access is denied. This happens with every device as some of the factors (extrinsic & intrinsic) are beyond its control. Therefore, while comparing, choose the one where the overlapping between genuine and impostor scores is minimal.



Acceptability & Liveness Detection Capability


Certain systems such as fingerprint readers have been in use for decades and people are rather comfortable with them; while, systems such as retinal & iris scanners though non-intrusive can reveal certain medical conditions to which people might object. Hence, acceptability becomes a concern here. Also, to distinguish between a genuine & fake identifier (like a fake finger) many scanners come with liveness detection hardware and software that are capable of determining whether the identifier presented is fake or not.



















There was a time when the choices related to purchasing a biometric device were limited and many desired features were either absent or extremely expensive for most of the commercial purposes. Hence, the implementation of biometrics to enhance security was limited to government agencies and national projects. However, in recent years the biometric industry has developed by leaps & bounds and has immensely improved its manufacturing & technological capabilities. The much needed ramifications of these changes are reduced cost and better integration with the other enterprise level systems that made biometric industry a multi-billion dollar industry in virtually no time.

Some factors that are helpful in purchasing the right biometric device are briefly discussed below.

Quality of Extracted Image

The process of biometric identification starts with the extraction of a biometric identifier such as fingerprints, iris patterns, veins, etc. with the help of a scanner. This extracted image of the identifier is then converted into digital templates using various techniques (vary from manufacturer to manufacturer) and consequently stored in a database for future matching. If the quality of the extracted image (and therefore of digital templates thus formed) is poor or not up to the minimal DPI (Dots Per Inch) required, then the matching process in most cases would lead to high FRR (False Rejection Rate). In case of fingerprint readers, there are many certifications such as FBI IAFIS IQS Appendix F & PIV-071006, WSQ, etc. that ensure the quality of reader is up to the standards required.

Processing Speed

The most significant feature of any biometric system (or any other security system) is its accuracy in determining who should get access to a facility and who doesn't. In addition to this, it's also important that these systems are capable of enrolling and matching biometric identifiers at an acceptable processing speed without compromising the accuracy of the process in any way whatsoever. This feature becomes even more important in big facilities where a large number of employees are enrolled and hundreds of matches happen every hour.

FAR & FRR

These two terms are critical when you are comparing two biometric devices. Let's understand their importance by taking the example of a fingerprint reader. During matching when the current template is matched with an existing template (in the database) of the same person, it's known as genuine matching and when compared with other templates, it's known as impostor matching. Ideally, genuine scores should be 100 % and impostor scores should be zero percent. In false acceptance rate (FAR), impostor scores are high enough that the matching algorithm takes them as genuine and allows access. Whereas, in false rejection rate (FRR), genuine scores are not high enough and are treated as impostor scores so that access is denied. This happens with every device as some of the factors (extrinsic & intrinsic) are beyond its control. Therefore, while comparing, choose the one where the overlapping between genuine and impostor scores is minimal.

Acceptability & Liveness Detection Capability

Certain systems such as fingerprint readers have been in use for decades and people are rather comfortable with them; while, systems such as retinal & iris scanners though non-intrusive can reveal certain medical conditions to which people might object. Hence, acceptability becomes a concern here. Also, to distinguish between a genuine & fake identifier (like a fake finger) many scanners come with liveness detection hardware and software that are capable of determining whether the identifier presented is fake or not.

This blog is listed under Development & Implementations and Peripherals Community

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