Facial recognition technology (FRT) is a biometric technology that analyzes and recognizes human faces based on unique facial features. It is capable of identifying individuals in photos, videos or scenarios in real time.
Using computer algorithms, specific facial landmarks such as the shape of the cheekbones and lip contour are mapped and translated into a code known as a facial trace. This technology relies heavily on various processes and techniques related to artificial intelligence.
In the case of verification or identification, the system compares the generated face print with a large database containing many existing face prints. It has gained considerable popularity and is used in many applications, including security systems, identity verification, access control, monitoring, and personalization.
The Ministry of Communications, specifically the Department of Telecommunications (DoT), recently created a facial recognition tool called Artificial intelligence and facial recognition based solution for SIM card subscriber verification (ASTR). This tool uses artificial intelligence (AI) to perform facial recognition for the purpose of verifying telecom subscriber SIMs.
· Know your mobile number (KYM): Find out the number of connections granted under your name by logging in with your mobile number. · ASTR – A solution based on artificial intelligence and facial recognition to verify telecom SIM subscribers…(3/3)
– DoT India (@DoT_India)
May 16, 2023
How does facial recognition technology work?
While many people are familiar with facial recognition technology through features such as FaceID that is used to unlock iPhones, it’s important to note that facial recognition has many different uses beyond just one use case. this particular tool.
In addition to unlocking the phone, facial recognition technology is also used to match the faces of people captured by the dedicated camera with the images included in the watchlist. These watch lists may include photos of individuals from a variety of sources, including those who are not suspected of or involved in any illegal activity. It is worth mentioning that facial recognition systems may differ in their specific implementation, but generally follow the following operating principles:
Step 1: Recording
1. Face detection: The algorithm scans image or video frames to locate and recognize human faces. It does this by analyzing patterns and features, such as pixel layout, color variations, and contrast.
2. Face alignment: After detecting a face, the technology will align the face in a normalized way. This step ensures that the face is in a consistent position and orientation, making subsequent analyzes and comparisons more accurate.
Step 2: Exploit
3. Feature extraction: The next step involves extracting key facial features from the aligned face. These features may include the distance between the eyes, the shape of the nose, the contour of the jaw, and the location of facial landmarks such as the eyes, nose, and mouth. This process converts visual information into a mathematical representation, such as a vector or pattern.
4. Face encoding: The extracted facial features are then converted into a unique face template or face embedding. This template is a compact numerical representation of recognizable facial features. Various algorithms such as deep learning techniques, neural networks or statistical methods are used to generate these representations.
Step 3: Compare
5. Face recognition: During face matching or recognition, the stored face samples are compared with the newly captured face template. Similarity between samples is calculated using mathematical algorithms, such as Euclidean distance or cosine similarity. If the similarity exceeds a certain threshold, the system treats the faces as a match, indicating the presence of a known person.
6. Database comparison: In many applications, facial recognition systems compare facial patterns with existing databases of celebrities. This database may contain images or samples of authorized persons, suspects or persons of interest. The system can quickly search the database for potential matches.
Step 4: Alignment
7. Decision and output: Based on the comparison results, the system makes a decision or gives an output. It may represent a match if the entered face matches a pattern in the database, or it may determine that the face does not match any known person. The output can be a simple binary (match/no match) or a ranked list of potential matches.
What are the advantages of facial recognition technology?
It offers several advantages:
1. Fraud detection: Verify the identity of real people in case of risky and suspicious activity.
2. Crime investigation: Facilitating crime investigation, identifying missing children/persons and unidentified corpses, and providing information for easier and faster analysis .
3. Banking: Withdraw cash at ATMs and tellers can use facial recognition to authorize payments.
4. Healthcare: Access patient records and simplify the patient registration process in a healthcare facility and automatically detect pain and emotion in patients.
5. Airport: FRT with electronic passport helps reduce waiting time and increase security.
6. Crime reduction: FRT makes it easier to find thieves, burglars and intruders. The mere knowledge of the presence of a facial recognition system can serve as a deterrent, especially for petty crime.
7. Faster processing: Facial recognition enables quick and efficient verification of a person’s identity.
In summary, it’s important to note that while facial recognition technology offers a number of advantages, it also raises concerns about privacy, security, and ethical issues. Appropriate regulatory and safeguards are needed to address these issues and ensure responsible use of technology.
See also: What is technology management?
Categories: Optical Illusion
Source: newstars.edu.vn