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Biometric applications can be seen everywhere in the "brush face" posture

  • Author:HFSecurity
  • Release on :2019-11-21
What we call "brushing face" is actually one of the ways in biometrics - "face recognition." The word biometrics is no stranger to today. From the previous sci-fi movies to the real-life applications, we are more or less exposed to biometrics. For example, the most widely used fingerprint unlocking function is A type of biometrics.

Biometric identification includes many methods, including the earliest signature recognition and fingerprint recognition that existed in ancient China (called "painting" in ancient times. The history is far before the Tang Dynasty. Although it was only a simple fingerprint comparison, it can be seen that the ancient Chinese have already Knowing that people's fingerprints and fingerprints are different, and now to the front of the iris recognition, facial recognition, gene recognition, gait recognition and ultra-frontal brain wave recognition. The basis of biometric identification is the physiological characteristics and behavioral characteristics of the human body. The physiological characteristics include fingerprints, facials, blood vessels, genes and other congenital features. These characteristics are inherently relatively stable and difficult to change. The behavioral features such as sound, signature, and gait are formed, and will change with the subject state, human changes, and environmental modes. It is not stable enough and will be easily imitated. Therefore, it is obvious that the identification of physiological features has higher safety and reliability in biometric identification, and the application value is relatively higher.



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In fact, the latest biometric identification methods are not as complicated as we think. In terms of the simple implementation principle, the following three parts are used. The first step is to extract the human body image through the photoelectric scanning sensor head. The second step will be The quantification, the world of computers always uses data to talk; the third step is to use the mathematical algorithm to process the extracted feature images, and finally generate feature templates to be compared with the pre-stored feature data of the human biometric database. Compare, and finally determine whether the match is based on the comparison similarity.

Thus, the entire identification system includes three processes of collecting samples, storing templates, and authenticating, and the process of authenticating records each input feature on a local or remote host, so the reference template is Each time the effective transaction process is dynamically updated, the system can be adapted to small changes caused by objective factors, such as changes in user age, makeup, and the like.

After understanding biometrics, let's focus on the "brushing face" recognition technology, and think about how your face can really be used as a card to brush, or a little unclear.

The specific details of the face recognition sample are to capture the image of the face or a series of images through a standard camera. After capturing, record some core points and record the relative position between the core points to form a template. The selection of the point and relative position is shown in the following figure:

The computer stores the obtained data in the database, and waits until the user inputs the information next time, and can compare the newly obtained information with the previously stored data, thereby achieving the purpose of confirmation.

One of the biggest highlights of facial recognition is that it is a non-contact recognition method, which is convenient and quick, and is not easy for the user to detect, so it is not easy to attract people. However, it also has the disadvantage that it cannot be ignored. The collection conditions are affected by light and facial coverings (beard, masks, sunglasses, etc.). The lighting conditions require that the light be bright and evenly applied to the person's face. As a result, facial recognition can be hindered at night or in places where the indoor light is not good. But overall, the accuracy of facial recognition is still quite high. Professor Tang Xiaoou of the Chinese University of Hong Kong gave a set of data: the computer recognition face accuracy rate reached 99.15%, and the accuracy of the naked eye recognition is about 97.52%, unexpectedly. It is even worse than the human eye. The reason why computer face recognition can be more accurate than the human eye is that the computer can pay attention to more key details and eliminate some interference factors through algorithms. Although there are still some loopholes in computer identification, the current high accuracy rate can be trusted. I believe that with the continuous improvement of technology, the existing loopholes will be compensated.


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Existing computer vision technology can identify individual faces and physiques and aggregate them on an individual basis. With the formation of 5G high-speed network channels and the maturity of AI and big data technologies, computer vision technology will undergo revolutionary changes, and face recognition will be more widely researched and developed. In China, cameras equipped with face recognition technology have sprung up on the streets of many big cities, and the scenes of paying for faces are everywhere. While face recognition is on the rise, there are concerns that the technology will be abused. So, what is the “treatment” of face recognition technology in other countries?

The United States is at the stage of legislative disputes as to whether face recognition should be used for law enforcement. At present, states such as Texas, Washington, and Illinois have enacted relevant laws, and some local governments have shown a tendency to be cautious and exclusive to face recognition technology. In January 2019, the center of Silicon Valley, San Francisco, issued a proposal called the Stop Secret Surveillance Ordinance, which prohibits the government from using face recognition technology. Some people clap their hands and think that privacy is protected. Some people vote with their feet, worrying that thieves are unscrupulous and claiming to move away without a camera. After more than three months of parliamentary discussions, the proposal was voted by 8:1. Recently, Microsoft deleted the face recognition database MS-Celeb-1M, which was composed of online pictures of 100,000 celebrities. It was used to train police officers and military-operated facial recognition systems.

Many shopping malls in the UK have enabled smart billboards with built-in face recognition technology to analyze the user's gender, age, and even income levels, and to present different advertisements for different passers-by. When more than 50% of the people passing by billboards are wealthy, billboards show advertisements for expensive products. Currently, there are more than 50 such large screens across the UK. The commercial application of face recognition technology has not been controversial in the UK, but in May 2019, face recognition technology was caught in the whirlpool of public opinion: a London citizen passed a camera with automatic face recognition function, because of the cover The face was fined £90; the first police face recognition case in the UK was opened, and the party claimed that the police station violated privacy. Many citizens in the United Kingdom believe that the use of face recognition technology by the government cannot be reassuring if the law does not ensure that people's rights to privacy and data security are properly protected.

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