Requirements for large-scale biometric systems

Nowadays the need for automated biometric identification systems is increasing in civil and forensic fields of applications. Fast and accurate identification becomes particularly critical for large-scale applications, such as passport and visa documentation, border crossings, election control systems, credit card transaction control and crime scene investigations. Many countries, including the US, European countries and others, incorporate biometric data into passports, ID cards, visas and other documents for use in large national-scale automatic biometric identification systems.

Automated fingerprint identification systems (AFIS) have been widely used in forensics for the past two decades, and recently they have become relevant for civil applications as well. Whereas large-scale biometric applications require high identification speed and reliability, multi-biometric systems that incorporate both face and fingerprint recognition offer a number of advantages for improving identification quality and usability.

Large-scale automatic biometric identification systems have a number of special requirements, which are different from those for small- or middle-scale biometric systems:

• The system must perform reliable identification with large databases, as biometric identification systems tend to accumulate False Acceptance Rate with database size increase and using a single fingerprint, face or iris image for identification becomes unreliable for a large-scale application. Several fingerprint images from person's different fingers or iris images from person's two eyes may be taken to increase matching reliability. Also, multi-biometric technologies (i.e. collecting fingerprint, face and/or iris samples from the same person) can be employed for greater reliability. A fused algorithm is used to create a single identification decision based on the results of those measurements.
• The system must show high productivity and efficiency, which correspond to its scale:
  • System scalability is important, as the system might be extended in the future, so a high productivity level should be kept by adding new units to the existing system.
  • The daily number of identification requests could be very high.
  • Identification requests should be processed in a very short time (ideally in real time), thus high computational power is required.
  • Support for large databases (tens or hundreds of millions of records) is required.
  • General system robustness. The system must be tolerant to hardware failures, as even temporary pauses in its work may cause big problems taking into account the application size.
• The system must support major biometric standards. This should allow using the system-generated templates or databases with systems from other vendors and vice versa.
• The system may need to match flat (plain) fingerprints with rolled fingerprints, as many institutions collect rolled fingerprint databases.
• The system must be able to work in the network, as in most cases client workstations are remote from the server with the central database.
• A forensic system must be able to edit latent fingerprint templates in order to submit latent fingerprints into the AFIS for the identification.

Despite all these requirements, the system price should be as low as possible.

Many existing AFIS are specialized for criminalistics or other particular applications and are quite expensive. Neurotechnology offers MegaMatcher SDK that includes technology and solutions for large-scale AFIS or multi-biometric fingerprint, iris, face, voice and palm print identification products. MegaMatcher SDK meets all of the requirements mentioned above, for a competitive price.

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