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Key Facts About Biometrics

What You Need To Know About Biometric Systems





The Key Facts You Need to Know About Biometric Systems

Although we, as humans, are designed to recognize one another easily at an early age, the human faculty of recognizing people is not foolproof. Similarities in appearance or behavior can easily mislead people. That’s why many companies nowadays make use of biometric recognition systems to authenticate the identity of authorized personnel.

Biometric machines revolutionized access control systems all around the world. It enabled organizations to automate the recognition of individuals based on their biological and behavioral characteristics. But like everything else, these systems have their own strengths and weaknesses. To give you an overview, here are the things top IT companies in the Philippines want you to know about biometric systems:

Biometrics and Human Identity

When we say biometrics, the first thing that comes to mind is usually human identity verification. Although that’s how biometric access control technology normally works, biometrics is not really a measurement of identity—it’s a measurement of similarity.

Biometric systems compare the biological or behavioral characteristics with those is stored in the records or archives of the database. Once scanned and the system detected similarity to the ones previously known, it will be considered to have come from the same individual. Hence, authenticating his/her identity verification in the access control system.


“Every individual has their own unique biometric characteristic.”


Fundamental Operational Concepts of Biometric Systems


Now that you have an idea about biometrics and human identity, it’s time that you understand how biometric identification systems operate. By learning how the system functions daily, you get to know the system better and understand whether this technology will work well for your company or not.

Every individual has their own unique biometric characteristic. In other words, the physiological imprints cannot be the same as any other. Because of that, biometric systems have been considered by experts as one of the most accurate identification systems at present. Now here are the fundamental operational concepts of the system will be outlined in detail.

  1. Sample Operational Process

Basically, the main components of a biometric identification system are the capture, the reference database, the matcher, and the action. Once a person provides his or her biometric sample to the sensor or scanner, the system captures it and then uses the mathematical algorithms necessary to compare references. After that process, the system then makes a recognition decision that determines the action that would be undertaken by the access control system.

  1. A Measure of Operational Efficacy

Operational efficacy has been established to cover multiple key aspects. Some of the renowned aspects are recognition error rates, acquisition cost, operational cost, maintenance cost, speed, data security, and usability. Although there are still a lot more factors that can measure operational efficacy, they are generally used to achieve the best-performing system for the company with operational and budgetary needs. Through this process, errors such as false acceptance and false rejections can be identified and improved with ease.

  1. Variability and Uncertainty

Matching algorithms play a significant role in how variabilities and uncertainties are handled. That’s why false rejections happen when there are some instabilities in the biological and behavioral characteristics provided.

For many years, it has been established by experts that the variability and uncertainty of biometric data truly have the ability to affect a system’s performance. Because of that, it’s clear that biometric applications generally need to capture multiple aspects of human traits in order to recognize a person’s identity more accurately.

  1. Within-Person and Between-Person Variability

As mentioned, there are some instances when there are instabilities in the biometric traits given by a certain person. That’s why it is necessary for biometric systems to have within-person variabilities and between-person variabilities.

In order to help you understand them better, here is the difference between the two:

  • Within-Person Variation

The within-person variation is also referred to as the intraclass variation. Generally, this variation occurs when a person interacts differently with the biometric sensor or when a person’s biometric feature changes over time.

In an ideal world, people must observe the same patterns every time in order to measure the biometric trait of each and every person. However, in the current practice today, different samples provide different patterns and digital representations. For this reason, manufacturers innovated ways to reduce or accommodate these variations. There are some companies that made use of the controlled acquisition of data, and there are also others that utilized the storage of multiple references for every user. Aside from that, there were also some that relied on the systematic update of references.

  • Between-Person Variation

The counterpart of the within-person variation is the between-person variation. This variation is sometimes referred to as the interclass variation or the person-to-person variability.

Over the years, it has been inherent that there are some individuals with similar biometric traits. One striking example of this is the identical faces of twins. This possibility led to a decrease of the between-person variation between two people.

In a nutshell, it is the magnitude of the within-person variation relative to the between-person variation that classifies the overlap of biometric measurements from different people. It is through these variations that biometric systems recognize individuals with acceptable accuracy.

If you take a look at large biometric systems, they attain their high identification accuracy by making the within-person variation smaller compared to the between-person variation. This is because the distributions of the observed biometric information among large groups of different people are likely to remain separated.

On the other hand, when the within-person variation is designed to be higher relative to the between-person variation, biometric systems tend to limit their capacity to recognize people. This is because high within-person variation impinges distributions on each other. With that said, it is evident that the number of enrolled subjects can’t be increased arbitrarily for a fixed set of features and matching algorithms without compromising its accuracy.

Comparison of Biometric Identification System Modalities

Generally, biometric modality pertains to the system designed to recognize a particular biometric trait. These biometric traits can be identified through a person’s face, fingerprint, palm print, hand geometry, gait, signature, or keystroke.

The presentation of an end user’s biometric feature can involve both biological and behavioral aspects. Hence, a system’s choice of modality clearly has the capacity to affect the technology’s design and performance.

Evidently, every modality has its own advantages and disadvantages. For this reason, it’s essential for business owners to choose the right modality for their biometric application.

To help you accomplish this, here’s a list of the biometric modality comparisons you should be aware of:

  • Universality

In this modality comparison, every individual that’s accessing the application is required to possess a certain trait.

  • Uniqueness

When it comes to uniqueness, the given trait needs to be sufficiently different among other members of the population.

  • Permanence

This requires the biometric trait of people to be invariant over time in order to match the set algorithm. In this modality comparison, a trait that changes significantly is not considered as a useful biometric trait.

  • Measurability

This factor entails the possibility of the acquisition and digitalization of the biometric trait using a suitable device. It is a requirement that the devices used do not inconvenience the users. Moreover, it is also necessary that the acquired raw data should remain amenable to processing in order to extract representative features.

  • Performance

This is the recognition of accuracy and the acknowledgment of the resources required to accomplish the accuracy necessary to meet the requirements of the biometric application.

  • Acceptability

In this factor, the individuals found in the target population will need to use the biometric application willingly by presenting their biometric trait to the system on their own.

  • Circumvention

This pertains to the security needs of a company to lower the chances of biometric trait imitations.

Business Perks of Using Biometric Identification Systems

The utilization of biometric identification systems gave organizations the capacity to repeatedly recognize people accurately. With this technology in place, business owners were able to customize automated actions based on their system’s recognition. Furthermore, biometrics technology has enabled its users to cut overall costs while reducing the chances of fraud, circumvention, and error. That said, it is undeniable that this technology helped organizations improve their scalability and physical safety.

Coping with the Biometric System’s Probabilistic Nature

Alongside the benefits that business owners reaped from biometric systems, is the prevailing need to cope with its probabilistic nature. This aspect of biometric systems is often left out from popular discussions of modern technology.

When you take a closer look at the biometric systems today, you will see that the match probabilities are only one part of the factors necessary to predict the true performance of these systems. By acknowledging this, you will be able to understand how to effectively use biometrics in your building. Furthermore, it’s also important that you don’t focus solely on the error rates found in your system. You need to keep in mind that these error rates only provide the conditional probability of the recognition or non-recognition of a specific biometric trait.