Guangdong Ankuai Intelligent Technology Co., Ltd.
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In a face recognition access control system, a camera captures an image of a person's face, and a software algorithm analyzes the facial features to create a unique biometric template. This template is then compared to a database of pre-authorized faces, and if a match is found, access is granted. If no match is found, access is denied.
| Screen size | 8-inch |
| Communication interface | RS232/RS485 |
| Face capacity | 20000(optional 50000) |
| Installation site | Wall, installation, gate installation |
| Dimensions | 246*21.5*123mm |
| System | Android 11 |
| Power supply | DC12V 2A |
| Touching | Selected touching |
| Working temperature and humidity | -15℃ to 55℃, <90℃RH |
| Texture | Aluminum alloy |
| CPU | RV1109 2 core 1.5GHz |
| Display screen | 8-inch high-definition IPS LCD screen, resolution 600*1024 |
| Camera | 200W live binocular camera |
| HDMI interface | Support |
| Optional accessories | Card reader, QR code reader, temperature |
1. Types of face recognition: There are different types of face recognition systems, including 2D, 3D, and thermal imaging. 2D face recognition relies on analyzing a two-dimensional image of a person's face, while 3D face recognition uses depth information to create a three-dimensional model of the face. Thermal imaging face recognition systems use thermal cameras to capture the heat signature of a person's face, which can be used to identify them.
2. Speed: Face recognition systems can process large amounts of data quickly, making them suitable for use in high-security environments where fast identification is essential.
3. False positives and negatives: Like all biometric technologies, face recognition can produce false positives and false negatives. A false positive occurs when the system incorrectly identifies an individual as someone else, while a false negative occurs when the system fails to recognize an individual who is in the database.
4. Ethics: The use of face recognition has raised ethical concerns around privacy, bias, and discrimination. The accuracy of the technology can be affected by factors such as skin colour, gender, and age, leading to potential biases in identification.
5. Advancements: Face recognition technology is constantly evolving, with new advancements being made in areas such as deep learning, machine learning, and artificial intelligence. These advancements are leading to more accurate and reliable face recognition systems, as well as new applications for the technology.
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