Facial recognition is a way of recognizing a human face through biometric software application capable of uniquely identifying or verifying an individual by comparing and analyzing mathematically patterns based on the individual’s facial contours and stores the data as a faceprint.
The facial recognition software uses deep learning algorithms to compare a live capture or digital image to the stored faceprint in order to verify an individual’s identity. There are multiple methods in which face recognition systems work.
Facial recognition work by compares the information with a database of known faces to find a match. Face recognition can help verify personal identity, but it also raises privacy issues
Facial recognition technology is the least intrusive and fastest biometric technology. It works with the most obvious individual identifier – the human face. Facial recognition is a biometric software application capable of uniquely identifying or verifying a person by comparing and analyzing patterns based on the person’s facial contours.
While face recognition has been around in one form or another since the 1960s, recent technological developments have led to a wide proliferation of this technology.
The human face plays an important role in our social interaction, conveying people’s identity. Using the human face as a key to security, biometric face recognition technology has received significant attention in the past several years due to its potential for a wide variety of applications in both law enforcement and non-law enforcement.
Your face is becoming the key to accessing your money, your devices and could mean the difference between freedom and imprisonment. Face recognition a feature that unlike fingerprints can be scanned at a distance, and it’s being used on a massive scale to electronically identify people as they walk past a camera.
How does Facial Recognition work
Every face has numerous, distinguishable landmarks, the different peaks, and valleys that make up facial features. These are called nodal points. The software identifies 80 nodal points on a human face. Nodal points are endpoints used to measure variables of a person’s face, such as the length or width of the nose, the depth of the eye sockets and the shape of the cheekbones.
The face recognition system works by capturing data for nodal points on a digital image of an individual’s face and storing the resulting data as a faceprint. The faceprint is then used as a basis for comparison with data captured from faces in an image or video.
The values measured against the variable associated with points of a person’s face help in uniquely identifying or verifying the person. With this technique, applications can use data captured from faces and can accurately and quickly identify target individuals. Facial recognition techniques are quickly evolving with new approaches such as 3-D modeling, helping to overcome issues with existing techniques.
Basic Steps Of Facial Recognition
1. Face Detection
It determines the location and size of human faces in digital images. The algorithm receives a photo as a set of data for the color value of each individual pixel. Then it looks for areas of contrasts, between light and dark parts of the image.
Upon the detection of each face-like image on a head-shaped form, it sends the face to the system to process it further. The system then estimates the head’s position, orientation, and size. Generally, a face needs to be turned at least 35 degrees toward the camera for the camera to detect it.
2. Face Capturing
The face capturing process transforms analog information (a face) into a set of digital information (data) based on the person’s facial features. Face Recognition software reads the geometry of the face by determining key factors, including the distance between the eyes, the thickness of the lips, the distance between the chin and the forehead, and many others.
Some advanced face recognition systems use hundreds of such factors. The result of this processing leads to the generation of what is called a facial signature.
3. Face Matching
The face matching process is the final stage in which newly acquired facial data is compared to the stored data if it matches with one of the images in the database the software returns the details of the matched face and notifies the end-user.
Pros of Facial Recognition
Increased Security – One of the biggest pros of facial recognition technology is that it enhances safety and security. The first thing to start with is surveillance. With the help of face recognition, it will be easier to track down any burglars, thieves, or other trespassers.
Fast and Accurate – The process of recognizing a face takes a second or less and this is incredibly beneficial for the companies. Facial recognition technology provides verification that is convenient, quick, and accurate. Although possible, it is very difficult to fool face recognition technology, which makes it beneficial in helping prevent fraud.
No Contact – Facial recognition is preferred over fingerprint scanning because of its non-contact process. People don’t have to worry about the potential drawbacks related to fingerprint identification technology, such as germs or smudges.
Automation of identification – Facial recognition is completely independent in the identification process and not only takes seconds but is also incredibly accurate. The 3D facial recognition technology and the use of infrared cameras significantly boosted the level of accuracy of face recognition and made it really hard to fool.
Cons of Facial Recognition
High Implementation Costs – Facial recognition requires top-quality cameras and advanced software to ensure accuracy and speed. However, Allied Market Research predicts that technological advancements are likely to reduce the prices of face recognition systems in the future.
Massive Data Storage – The video and high-quality images required for facial recognition take up a significant amount of storage. In order to face recognition systems to be effective, they only process about 10 to 25% of videos.
Breach of privacy – With the help of facial recognition technology, the government can actually track down people like you: anytime, anywhere.
Facial Recognition Limitations
- Obstruction – As you’d expect, sunglasses and other accessories can trip up facial recognition software.
- Poses – Facial recognition works best with a neutral, frontward-facing image. A Tilt or turn of the head can make face recognition difficult, even for IR-based recognition software. Additionally, a smile, puffed cheeks, or any other pose can change how a computer measures your face.
- Light – All forms of facial recognition rely on light, whether it’s visible spectrum or IR light. As a result, weird lighting conditions can decrease the accuracy of facial identification. This may change, as scientists are currently developing sonar-based facial recognition technology.
- Database – Without a good database, facial recognition can’t work. Along these same lines, it’s impossible to identify a face that hasn’t been identified correctly in the past.
- Data Processing – Depending on the size and format of a database, it can take a while for computers to identify faces correctly. In some situations, like policing, limitations in data processing restrict the use of facial identification for everyday applications.
Who uses facial recognition
- Government – Every government stores and use facial data in a various way depending on what they want.
- Mobile phone makers – A variety of phones including the latest are now using face recognition to unlock phones.
- Colleges- To making schools and collages safer, face recognition has the potential to track students’ attendance.
- Social media companies – Facebook and other social media companies use face recognition technology to automatically recognize when Facebook members appear in photos.
- Businesses – Some companies have traded in security badges for facial recognition systems.
- Religious groups – Not Every religious group but Churches have used facial recognition to scan their congregations to see who’s present.
- Retailers – Retailers can combine surveillance cameras and face recognition to scan the faces of shoppers.
- Airlines – Airlines have already started using facial recognition to help people check bags, check into flights and board planes faster.
- Advertisers – Face recognition has the ability to make advertising more targeted by making educated guesses at people’s age and gender.