What is Facial Recognition System?
Facial recognition or Face recognition is an identification technique that uses a biometric method to identify an individual by closely observing and comparing a live capture or a digital image of that individual with the image of that individual stored in a facial database for authentication. The Face recognition systems are widely used for ensuring the security of the data accessed by various users.
Face recognition system is an impeccable technique to measure and match the unique characteristics extracted from an image with the previously stored data to identify and authenticate the credibility of an individual.
Applications of Face Recognition System
Areas of application
● Public security system
● Developing more specific business applications
● Airport security system
● Financial services
● Law enforcement
● Driver’s Licenses and Passport
● Working staff surveillance system
● Access control system
● Banking environment application
● Shopping mall customer analysis
The Face Recognition System is indeed a boon to provide and assure the safety of access to any kind of dataset. The Face recognition technology can be used for numerous purposes such as implementing access control in areas that could be prone to risks, residential areas for preventing the chances of theft cases, and much more.
In the past few years, the face recognition system has been used primarily by the Law Enforcement Agencies as a crime fighting tool, often to capture the faces of random people in crowds. Also, some government agencies have been using the face recognition systems to eliminate fraud voting and ensure security.
However, in the current era whereby these systems are being used in many areas of applications since the systems become less expensive.
Face Recognition System can be implemented across a wide spectrum of applications that are discussed below:
1. Preventing fraudulent transactions: Face recognition promises to reinforce security in significant ways such as securing ATM transactions and check-cashing operations. The system is capable of instantly verifying the customer’s face. Just when the customer accords, the ATM kiosk captures a digital image of the person doing the transaction. This helps in preventing customers from fraudulent transactions since the system generates a faceprint of the photograph to eliminate identity theft. By using the face recognition system, one doesn’t need to keep a picture ID or a PIN, it simply takes a picture and verifies a customer’s identity.
2. Residential Security: Alert homeowners about approaching the person.
3. Attendance and tracking information of the staff: For many entrepreneurs, time attendance and tracking are very important factors. No doubt, you want to avoid time card fraud and you may need to carefully track employees and visitors for security purposes.
4. The world of Games: The face recognition system has come up with a whole new dimension in the world of gaming. The Kinect motion gaming system developed by Microsoft has given the Xbox 360 a whole new lease of life with its advanced motion sensing capabilities and opened up gaming to the audiences by completely doing away with hardware controllers.
Meanwhile, Viewdle has recently launched a game in which it undergoes a process to identify whether the user is a human being or a robot or a vampire using face recognition system, setting the stage for a battle between the two species.
5. Automated tagging facility: The most famous social networking site Facebook facilitates automatic tagging of the people in a picture with the help of facial recognition software. Here’s a detail of how facial recognition works in Facebook- Each time an individual is tagged in a picture, the software application stores information about that individual’s facial characteristics. When the collected data becomes sufficient to recognize an individual, the face recognition system uses that data to recognize the same face in different pictures and can also suggest their names for tagging that person in a picture you’re going to post.
Facial Recognition is a brilliant and powerful tool that is slowly making its way in the world of technology. Although fingerprint biometrics is a popular biometric method, facial biometric is also rapidly becoming a preferred choice as well in the era of tech services. Biometric technology has been greatly ameliorating since the past few years, therefore making facial solutions more infallible than ever. Biometric imaging has made itself an excellent and credible choice for various security software.
PROS and CONS of Facial Recognition System
Benefits of using a Face Recognition System
1. Betterment in Security — The face recognition system provides time attendance tracking which helps you not only in tracking the employees of the organization but the visitors as well along with ensured security. In fact, the incoming visitors can be added to the system and tracked throughout the premises. Anyone whose information is not stored in the system will not be allowed to gain access.
2. Automated Facial System — One of the most attractive and reliable reasons behind implementing Facial systems is that these biometric systems are automated i.e they don’t necessarily need someone to operate or monitor them 24*7. Thus it becomes easy to keep the system working for all day long without any need for personnel to operate the system and look after its performance.
3. Ease of Integrating with the existing software — Integrated Biometric face recognition systems are very easy to program into your work environment and the computer systems in your companies. They can easily work with existing software that you have been using in your company.
4. Successful performance — Facial recognition technology has a huge success rate in today’s era where technology has proved to be the soul of the market mainly with the emergence of 3D face recognition technologies. It is almost impossible to misguide the system about the information that is being stored, with this it can be assured that the security system that will be implemented will be successful in maintaining the tracking time and attendance with safety.
Limitations of Face Recognition System
1. Picture Quality — Picture quality is a major factor to see how well facial-recognition algorithms work. The picture quality of the scanning video is not as good as compared to that of a digital camera. Low-quality pictures in the facial database can lead to a situation whereby an individual could be mistaken for another by the facial recognition software.
2. Changes in Appearance of an individual — There are chances that a person might look different from the picture that has been previously stored in the facial database to identify her/him uniquely. Using infrared or augment facial recognition software does not necessarily eliminate the identification issues that might be created due to a slight or significant change in the appearance of an individual. Changes such as getting a haircut cut or wearing a scarf or veil or sunglasses while facing the camera probably affect the efficiency of the software to identify an individual by comparing the live capture with the stored picture in the facial database. Facial recognition software doesn’t work well in such conditions because these all things partially obscure the face of the individual.
3. The requirement of high-quality equipment/tools: Implementing/ installing facial recognition system in an organization requires massive investment to be done to install cameras that can capture high-quality images for maintaining a database that contains information about an individual as digital images. In a similar way, the software infrastructure must be capable of processing the image instantly and recognizing an individual by measuring and matching their unique facial characteristics. If it is not so then this might lead to waiting time that is not really acceptable in today’s time where everything has to be speedy and instant.
The Facial Recognition System (face recognition system) is a computer application developed to facilitate identification or verification of an individual from a digital image or a video by measuring and matching the unique facial features with the previously stored image in the database.
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