After more than ten years of technological development and application market cultivation, today's biometric technology has been applied in large scale in many application fields. As far as the Chinese market is concerned, the application of biometrics technology has mainly been based on fingerprint recognition technology, one of its sub-technologies. In the Chinese market, fingerprint recognition applications account for the majority of market share (according to 2007). Data, China's biometrics market, fingerprint recognition applications account for more than 90% of the market share). This is far from the general trend of global biometrics application. However, we are also pleased to see that some new technologies, such as face recognition technology, have been applied in the Chinese market in the past one or two years, and their market potential cannot be underestimated. This paper will discuss the two most significant developments of biometrics from the perspective of technology and application: face recognition, and multiple biometrics. As far as the global market is concerned, face recognition is the second largest biometric technology after fingerprint recognition. In general, face recognition technology is mainly used in the following three areas, in which face recognition has unique advantages: 1) Large file management systems, such as driver's license and passport management systems; 2) Automatically monitor the target person through the camera monitoring network according to the blacklist; 3) Access control system. In fact, face recognition has great potential in personal use, business, and government applications. This technology is still evolving and developing, and its application is becoming more and more popular. With current technology and product levels, face recognition systems are fully capable of being implemented and applied at a cost level that customers can receive. Simply put, face recognition technology is to first record the characteristics of the face (whether it is collected on site or from photos), and then automatically and accurately identify whether it is used (re-collecting face images or submitting photos). same person. Like other biometrics, the face recognition system is the first to generate a feature template for a face and store it in a database. These templates will be used to match the template submitted for comparison. Usually, when two templates are compared, if the similarity exceeds the system preset threshold, the system considers the comparison successful. -- These two templates are from the same person. There are also different types of face recognition technology, including recognition based on facial features, recognition based on skin texture analysis, and even recognition based on face temperature patterns. The latest technology uses a three-dimensional image of a face to create a template--a technique for automatically generating three-dimensional image modeling from a two-dimensional image of a human face, and a technique for truly modeling a face and a head image in three dimensions. Of course, the commonality of these technologies is that they are based on face image information. In addition to this common starting point, they differ greatly. Because face recognition relies on image information of the camera/photo, it is possible to understand how much the image quality affects the accuracy of the system. The quality of live face images is affected by many factors: ambient light, camera image resolution, lens focal length and depth of field parameters, the speed of the target's face, and many other factors. In addition to image quality, the second major factor affecting the reliability and accuracy of face recognition systems is the level of skill in the recognition algorithm itself. “Cameras and scanners are like eyes, but recognition algorithms are the brains of face recognition systems,†said Algimantas Malickas, CEO of Neurotechnology Ltd, a core algorithm for many biometric technologies. “Without high-quality algorithms, a face recognition system is not reliable. For biometric applications, system reliability is undoubtedly the most important consideration for customers.†Human factors are also an important factor affecting the accuracy of face recognition technology. For example, the use of the camera, lighting conditions and changes in the shadow of the target person's face may make the performance of the face recognition algorithm greatly compromised. Algorithm vendors have been looking for ways to reduce the negative effects of these human factors, and have developed a number of innovative methods and techniques. How to ensure that the right camera and algorithm are chosen in a particular application is also very particular. Different applications require different technologies, and many camera products and face recognition algorithms on the market do not all have the same quality. Soft Starter,Ac Motor Soft Starter,Soft Starter For Machinery,3-Phase Soft Starter Zhejiang Kaimin Electric Co., Ltd. , https://www.ckmineinverter.com