Enrollment. As shown in Figure 1, the biometric sample of the individual is captured during theenrollment process (e.g., using a sensor for fingerprint, microphone for speaker recognition, camera forface recognition, camera for iris recognition). The unique features are then extracted from the biometricsample (e.g., image) to create the user’s biometric template. This biometric template is stored in adatabase or on a machine-readable ID card for later use during a matching process.

Matching. Figure 2 illustrates the biometric matching process. The biometric sample is again captured.The unique features are extracted from the biometric sample to create the user’s “live” biometric template.This new template is then compared with the template(s) previously stored and a numeric matching(similarity) score(s) is generated based on a determination of the common elements between the twotemplates. System designers determine the threshold value for this verification score based upon thesecurity and convenience requirements of the system.

Identification (one-to-many or 1:N comparison) determines if the individual exists within an enrolledpopulation by comparing the live sample template to all stored templates in the system. Identification can confirm that the individual is not enrolled with another identity or is not on a predetermined list ofprohibited persons. The biometric for the individual being considered for enrollment should be comparedagainst all stored biometrics. For some credentialing applications, a biometric identification process isused at the time of enrollment to confirm that the individual is not already enrolled.

Verification (one-to-one or 1:1 comparison) determines whether the live biometric template matcheswith a specific enrolled template record. This requires that there be a “claim” of identity by the personseeking verification so that the specific enrolled template record can be accessed. An example would bepresentation of a smart card credential and matching the live sample biometric template with the enrolledtemplate stored in the smart card memory. Another example would be entry of a user name or ID numberwhich would point to an enrolled template record in a database.

The selection of the appropriate biometric technology will depend on a number of application-specificfactors, including the environment in which the identification or verification process is carried out, the userprofile, requirements for matching accuracy and throughput, the overall system cost and capabilities, andcultural issues that could affect user acceptance. The table shows a comparison of different biometrictechnologies, with their performance rated against several metrics.

A key factor in the selection of the appropriate biometric technology is its accuracy. When the livebiometric template is compared to the stored biometric template (in a verification application), a similarityscore is used to confirm or deny the identity of the user. System designers set the threshold (match or nomatch decision point) for this numeric score to accommodate the desired level of matching performancefor the system, as measured by the False Acceptance Rate (FAR) and False Rejection Rate (FRR). TheFalse Acceptance Rate indicates the likelihood that a biometric system will incorrectly verify an individualor accept an impostor. The False Rejection Rate indicates the likelihood that a biometric system willreject the correct person. Biometric system administrators will tune system sensitivity to FAR and FRR toget to the desired level of matching performance supporting the system security requirements (e.g., for ahigh security environment, tuning to achieve a low FAR and tolerating a higher FRR; for a highconvenience environment, tuning to achieve a higher FAR and a lower FRR).

Some of the accuracy and usability limitations imposed by the use of a single biometric modality can beovercome by using multiple biometric modalities. Multi-modal biometrics enhance the overall matchingaccuracy through the use of multiple and independent biometric measurements. For example, thesimilarity score from a fingerprint measurement can be mathematically “fused” with an independentmeasurement of the vein pattern in the finger to yield a higher level of confidence in the identity of aperson.In addition, multi-modal biometrics can provide a solution for those individuals who are unable to presenta suitable biometric sample in one modality. An example would be offering the option to present either afingerprint or iris for authentication. A person who has poorly defined fingerprint patterns due to age,occupation, or medical condition would be given the choice to enroll and use iris as their biometricmodality of choice. If both sensors are present, the user can use whatever modality that they are bestsuited for. In this situation, there is no fusion of independent biometric measurements.As can be seen in Figure 3, multi-biometric systems can incorporate information from multiple modalities,instances, algorithms, sensors, samples, or any combination of the five8. Arguably, such systems mayalso include other sources of information, including biographic or travel document-based information.

Biometrics and security have become an indispensable part of self-service, and Huabiao Technology has always adhered to security as its bottom line, providing users with safe and efficient services.For more information about the company and its offerings, visit the About Us page or reach out through the Support page.