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 real-time situations.
Using a computer algorithm, specific facial landmarks such as cheekbone shape and lip contour are mapped and translated into a code known as a fingerprint. This technology depends heavily on various processes and techniques related to artificial intelligence.
In the case of verification or identification, the system compares the generated face mark with a large database containing many existing face marks. It has gained considerable popularity and is used in a wide variety of 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 Solution supporting artificial intelligence and facial recognition to verify telecommunications SIM subscribers (ASTR). This tool uses artificial intelligence (AI) to perform facial recognition for the purpose of verifying telecom SIM subscribers.
· Know your mobile phone (KYM): Know the number of connections granted under your name by logging in with your mobile number. · ASTR- Artificial intelligence & identity powered solution face to verify telecommunications 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 like the FaceID that is used to unlock iPhones, it’s important to note that facial recognition has many different uses beyond the case. this particular use.
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 on the watch list. These watchlists 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 they generally follow the following operating principles:
Step 1: Shoot
1. Face recognition: Algorithm scans image or video frames to locate and recognize human faces. It achieves this by analyzing patterns and features, such as the arrangement of pixels, color variations, and contrast.
2. Face alignment: Once a face is detected, the technology will align it 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: Unzip
3. Feature extraction: The next step involves extracting key features of the face from the aligned face. These features may include the distance between the eyes, the shape of the nose, the contour of the jawbone, and the location of facial features such as the eyes, nose, and mouth. This process converts visual information into mathematical representations, such as vectors or patterns.
4. Face encoding: The extracted facial features will then be converted into a unique face template or face embedding. This template is a compact numerical representation of the distinguishing features of a face. 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 templates are compared with the newly captured face template. The similarity between samples is calculated using a mathematical algorithm, such as Euclidean distance or cosine similarity. If the similarity exceeds a certain threshold, the system considers the faces as a match, indicating the presence of a known individual.
6. Database comparison: In many applications, facial recognition systems compare facial patterns with existing databases of known individuals. This database may include photographs or samples of authorized individuals, suspects or persons of interest. The system can quickly search the database to find potential matches.
Step 4: Match
7. Decision and output: Based on the comparison results, the system makes a decision or gives an output. It can indicate a positive match if the input face matches a pattern in the database, or it can determine that the face does not match any known individuals. The output can be a simple binary (match/no match) or a ranked list of potential matches.
What are the benefits of facial recognition technology?
It offers several benefits:
1. Fraud Detection: Verify the identity of an actual person in the event of risky and suspicious activity.
2. Crime investigation: Facilitating crime investigation, identifying missing Children/persons and unidentified corpses, and providing information for easy and quick analysis than.
3. Banking: ATMs and cash registers can use facial recognition to approve payments.
4. Healthcare: To gain access to patient records and streamline the patient registration process in a healthcare facility, and automatically detect pain and emotion in patients.
5. Airport: FRT in the form of an electronic passport reduces waiting times and improves security.
6. Reduce Crime: FRT makes it easier to track down thieves, burglars and trespassers. Unique knowledge of the presence of facial recognition systems can act as deterrents, especially for petty criminals.
7. Faster processing: Facial recognition allows for 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 benefits, it also raises concerns regarding privacy, security, and ethical considerations. Appropriate regulatory and protective measures are needed to address these issues and ensure responsible use of technology.
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Categories: Optical Illusion
Source: pagasa.edu.vn