The Differences Between Biometric Identification Techniques
As the need for safety and security skyrocketed all over the world, it became a common scenario to find biometric identification systems in place almost everywhere. With the existence of
, many business owners were able to foster a secure working environment for their employees. Furthermore, the introduction of biometric technologies like fingerprint attendance systems in the business world was able to promote a more efficient and accurate system to determine the authenticity of a users’ identity.
In this blog, the different types of biometric identification techniques will be discussed thoroughly. But before anything else, let’s have a brief background about biometric systems.
Brief Background About Biometric Identification Systems
Basically, a biometric identification system is a pattern recognition system. With this technology in place, your business’ security system will be able to recognize a person’s identity based on their physiological or behavioral characteristics. Aside from that, this innovation also enables organizations to reduce the search space and data retrieval time to a minimum.
At present, the innovators of biometrics technology introduced several identity classification techniques to the public. One example of this is the classification of face images based on a person’s age. With this technique, organizations gain the capacity to classify input images into babies, adults, senior adults.
If you want to learn more about the different types of biometric identification techniques, then the next section of the blog is made for you.
Different Biometric Identification Techniques
Evidently, biometric systems involve a lot of comparisons in the database in order for it to function. When the database size increases, the data retrieval and search times grow alongside it. For this reason, this technology makes use of identification techniques to reduce the search space necessary for a matcher to operate.
To delve into detail, here’s a list of identification techniques you should know about:
This technique pertains to the designation of a certain object physically to a set of predefined categories. In other words, a biometric technology that makes use of the classification technique identifies people based on their biometric pattern, texture, or other soft biometric attributes. Furthermore, when you deploy this type of biometric technique, you divide your organization’s database into multiple groups that have their own homogeneous characteristics.
Here are a few of the commonly used classification techniques at present:
This classification technique classifies people through face images. That said, this technology can identify people based on their age, gender, ethnicity, etc. With the biometric systems available today, it is now possible to train the classification of algorithms in greyscale images to represent a point in the image space. Furthermore, it also allows security systems to use statistical classification algorithms in order to enable automated gender classification, skin wrinkle analysis, and many more.
More often than not, IT professionals from reputed managed services consider fingerprint classification as one of the most reliable identification methods. Generally, fingerprint biometrics can be classified into known pattern classes. Some of the common pattern classes are arch, tented arch, radial loop, ulnar loop, twin loop, and whorl.
Other than the ones mentioned above, another popular identification technique nowadays is the iris classification. With the help of an iris scanner, the iris is exposed to subtle infrared rays in order to analyze its features accurately. In the present time, there are more than 200 points that can be used for comparison in a person’s iris. This includes rings, freckles, and furrows.
Many fields these days make use of the data clustering technique in order to perform statistical data analysis. Clustering often involves machine learning, pattern recognition, data mining, bioinformatics, and data analysis. In other words, it is a segmentation of objects that share a common train into multiple groups or dataset subset partitioning.
Basically, data clustering algorithms are classified into hierarchal or partitional. To enlighten you on the difference between hierarchal and partitional clustering, here’s a brief description of the two:
Hierarchical Clustering Algorithm
When it comes to hierarchal algorithms, you will see that they can be divisive (top-down) or agglomerative (bottom-up). Divisive algorithms usually start with the whole set and then proceed to its successive division into smaller clusters. Meanwhile, agglomerative algorithms start with each element as a separate cluster before it merges them into larger clusters.
Partitional Clustering Algorithm
A partitional clustering algorithm creates partitions of the data found in a specific database. In here, each cluster will be optimizing a clustering criterion like the minimization of a squared distance’s sum from the mean of each cluster. According to IT professionals, one of the issues they encountered in this type of clustering algorithm is its high complexity.
The indexing technique is the logical partitioning of the data space. This search space approach pushes companies to make use of a reduction tree structure for them to organize data effectively. In most cases, each leaf node stores at least one biometric template. For this reason, only the templates that have similar index values can be considered as the search space.
Over the years, it has been inherent that biometric data is multidimensional. Because of that, it’s important that the indexing technique you use supports multidimensional data. One of the most feasible indexing techniques for biometric databases in the present time is the Pyramid technique. The concept of this technique is based on the spatial-hashing of high-dimensional data into a single value. In other words, the pyramid technique was designed to enable organizations to work on higher-dimensional spaces that have been tested on a 100-dimensional data set.
4. Hash Function
The hash function is also known as the hash table or hash map. According to experts, the hash function is renowned to be a data structure that can associate keys with corresponding values. In other words, it transforms keys into a hash with the help of a hash function. By calculating keys using feature values and key generated identifiers, you will see that hashing can do a lot of things for biometric data.
Additional Information: Top Biometric Identification Trends in the Business World
As you can see, the integration of biometric authentication in daily tasks and operations created a huge impact on the way the business world was revolutionized. This is especially true in the aspect of security and convenience. With the prevalent business perks that it delivered to its end-users, it became prevalently used across organizations.
When you take a look at the technologies available today, you will see that there is now a widespread of powerful technologies like smartphones that make use of biometrics. As more and more manufacturers compete with one another to innovate their own biometric identification system, they dedicate themselves to develop new biometric trends in the future.
If you’re still not convinced, here’s a list of the top 10 advantages business owners can get from biometric technology:
- Over the past few years, biometric identification technology has proven itself helpful in different industries when it comes to ID verification. Some of the organizations that make use of this technology are the government, banking and financial institutions, and other areas that require high security.
- Apart from ID verification, one of the renowned advantages of using biometric technology is its high accuracy in individual identification. Generally, biometric identification relies on unique physical traits like iris patterns, palmprints, fingerprints, and many more. Hence, this technology is undeniably an accurate technique that businesses can use to authenticate end-users.
- Beyond any doubt, it’s impossible for biometric characteristics to be conjectured or stolen. For this reason, biometric technology has been recognized by experts as an effective tool that provides a superior level of security to its users.
- Every person’s biometrics, whether physical or behavioral, are less likely to undergo sudden changes and damages. Hence, it makes biometric technology an ideal access control system to ensure the safety and security of your company.
- One of the renowned advantages of using biometric technology is its dependability. According to the organizations that utilized this technology, identity authentication became less time consuming and inexpensive because of biometrics.
- Other than the ones mentioned, biometric technology has also been used in a wide range of industries like civil ID, business, schools, financial industries, and healthcare. At present, there are several countries that are now using biometric technology for their national ID, voter registration, national healthcare, and e-passport projects.
- Over the years, biometric technology has been effectively implemented in forensics. As a matter of fact, this technology has proven itself helpful in ensuring criminal identification and prison security.
- As mentioned, biometric identification technology has assisted organizations in providing accurate verification to the users that accessed specific accounts. As more and more businesses make use of the internet, biometric identification technology gradually became one of the most suitable solutions in securing mobile transaction identification.
- In the present time, biometric technology has been used to deter unauthorized access to ATMs, smart cards, desktop computers, workstations, and computer networks. For the past few years, it has been a great help for a lot of users worldwide.
- Unlike biometric technology, passwords and PINs can easily be hacked or forgotten. That’s why it’s been recommended by IT professionals that you make use of biometric technology to enhance your access control system.