What is Face Recognition?
Face recognition technology identifies a person based on their facial features, using recognition software to confirm an identity. This type of software is considered to be a biometric technology, as it measures a person's own biometric features to determine who they are. Over the last few years, we have become much more well acquainted with biometric technologies as devices like mobile phones and computers have taken to using them as an added layer of security.
From fingerprints to face recognition software, biometric scanners have become extremely common as they ensure security and protection in a way that passwords are not able to provide (no one can learn or steal your fingerprint or face structure). Face recognition and other biometric technologies are also commonly used in law enforcement both when it comes to the victims and criminals of crime. This database of information has been imperative in keeping track of and recording criminals.
How Does Face Recognition Work?
So now that we know what face recognition is, it is time to look at how this nifty technology actually works. Face recognition systems work by creating numerical patterns and values based on your facial features. These features become recognisable by the technology through the processing of these unique features when a person presents their face in front of a face recognition search technology, which will then process your features.
While this sounds like it would take some time to work, face recognition processes happen in a matter of seconds, determining who the person in front of it is and if it has the matching information loaded. The results of face recognition may differ depending on who is using it and what it is being used for. If you are looking to open a mobile device using facial recognition, if your face is loaded in the database of the device it will unlock, and if not, it will not be able to process the request.
The following is a look at the step-by-step process of how face recognition works and how the results are presented.
- The first step is the detection of a face. The face has to be presented in such a way that the facial features can be detected, but different kinds of face recognition projection tools may have different capabilities. A face recognition software used by the FBI for example would be much more advanced than the ones we use on our mobile devices.
- Following on from this, the software will analyze facial features that are distinguishable and unique, coming up with geometric measurements. An example of what it would measure is the amount of space between your eyes.
- Once your face has been analyzed, it will turn the data that it has captured into numerical values.
- The numerical values will then be compared to what is loaded within the face recognition database to determine if a match can be found.
Who Uses Facial Recognition?
Face recognition was once considered to be a very advanced type of technology that was only used in security and law enforcement. While these technologies are still used within these industries, face recognition is much more commonly used today. If you have the latest versions of mobile devices, they would more than likely include face recognition within the security features, allowing you to choose who is able to open a device based on whether or not their face recognition has been included within the settings. Face recognition has grown in popularity and many people use this kind of technology for many different reasons every day.
What Are Some Examples of Facial Recognition?
As has been mentioned, face recognition software is used within many different industries for different reasons. Law enforcement uses face recognition often to search through different databases that have been compiled for different reasons. Law enforcement agencies will have different databases set up for different things, one database could be for sex offenders and another for missing persons. By running a face through a face recognition program and then comparing results with faces loaded in databases, you may find who you are looking for. This kind of technology is extremely beneficial in these cases and when it comes to looking at face recognition examples and how this software is used, law enforcement agencies are likely to use this for many different cases.
Rulta is a company that has also developed technology through the use of face recognition software. When scanning content online in the form of images, Rulta uses technology to find certain images of certain people. If, for example, you are on OnlyFans, Rulta will be able to scan websites for images of your face to find any stolen content. This has become extremely beneficial as it helps to protect images rather than just protecting written content. As sites like OnlyFans become more and more popular, Rulta has developed this face recognition software as a way to better protect users!
What are The Effects of Using Facial Recognition?
- Security: Whether facial recognition is being used to keep your personal phone secure or being used to keep track of criminals, this technology has many benefits when it comes to increased security. This software makes it far easier to track down criminals and compare crime scene images to a database that contains hundreds of thousands of faces. Even a crime scene picture that has been compiled by a witness could be run through more advanced facial recognition technology and come up with a match!
- Efficient: No matter what facial recognition is being used for, it increases efficiency and allows for data to be processed quickly.
- Breach of Privacy: Facial recognition is often used in public spaces, with images of people being taken and unknowingly stored in databases. While this is effective when it comes to tracking down criminals, for the average person, it is an extreme breach of privacy. Your image could be stored in a database without you even being aware that it has been taken, which is quite scary to consider!
- Storage of Data: As stated above, there are millions of images of people that have to be compared in order to create effective databases. This takes up a ton of storage, leading to massive data warehouses that need to be developed for these images.