Samsung Galaxy Note7, which was released recently in China, mainly features iris recognition, and fingerprint recognition has become a standard for smartphones. A wide variety of biometric technologies are used in smart devices, in which speech semantic recognition and image recognition cover artificial intelligence technology. These technologies have become a new trend in human-computer interaction, and are the underlying technologies that all types of terminals need to do in the future.
Rapidly growing market
According to the China Foreground Industry Research Institute, the global market for biometrics grew at an average annual rate of 21.7% from 2007 to 2013. In 2015, the global market for biometrics technology will reach 13 billion U.S. dollars, and will reach 25 billion U.S. dollars in 2020. The average annual growth rate in five years is about 14%.
From 2015 to 2020, the market size of each segment is: fingerprint (73.3%), voice (100%), face (166.6%), iris (100%), and others (140%). Among the many biometric technologies, face recognition ranks first in terms of growth, and the market for face recognition technology is expected to rise to $2.4 billion by 2020. We expect the market size to be larger than expected in the case of smart terminals penetrating face recognition.
Five biometric classifications
The five major biometrics have their own characteristics, but from the perspective of market share, the most likely to stand out after fingerprint identification is face recognition. The speed of adopting face recognition technology by terminal consumer electronics manufacturers may approach the current market share of fingerprint recognition within two years. In particular, Alipay, brokerages, and bank-based financial services institutions have started to use face recognition for account opening, transfer, and payment in the past year. In the case of China Merchants Bank, face recognition can realize more than 500,000 transfers on the mobile phone. Its safety is recognized.
1. Fingerprint recognition is the most widely used biometric technology at present, with mature technology and low cost. It is widely used in attendance, access control and other identification. However, it is easy to copy, and the fingerprint is worn to affect the recognition accuracy.
2. Iris recognition The feature template is formed by using the features of the iris region (rings, wrinkles, spots, crowns) in the human eye image, and the recognition is completed by comparing the feature parameters. The method has high recognition accuracy and is not easy to counterfeit, but the related equipment is expensive.
3. Speech recognition By analyzing the unique characteristics of speech for identity verification, the device has a large range of distance and easy installation, but the recognition accuracy is low, which may be deceived by recording, and is susceptible to background noise, physical condition, emotion and other factors.
4. Signature recognition is a biometric technology based on behavioral characteristics, which is authenticated by analyzing handwriting, pressure, and writing speed. However, signatures can be highly counterfeit, and signature tools, emotions, etc. can interfere with signature recognition.
5. Compared with other biometric methods, facial recognition has the advantages of naturalness and undetectedness. Naturalness means that the recognition method is the same as that used by humans for individual identification. Humans also distinguish and confirm other individuals by observing information such as faces and sounds. Therefore, fingerprint recognition, iris recognition, and the like are not natural. The undetected feature makes the identification method difficult to make people conflict. The visible image can be used to obtain facial image information, while the fingerprint recognition or iris recognition needs to use electronic pressure sensor or infrared to collect fingerprint and iris image. In the process of collection, the identity information is It is possible to be copied.
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