In today's information age, how to accurately identify a person's identity and protect information security has become a hot topic that has attracted widespread attention from all sectors of society. Traditional identity authentication is becoming increasingly difficult to meet practical needs due to its susceptibility to forgery and loss. Currently, the most convenient and secure solution is undoubtedly biometric technology.
Multimodal biometric technology is a system that can register, verify, and recognize multiple physiological or behavioral features. Human body recognition based on multimodal biometric recognition is becoming an emerging trend, and the key reason for combining different modalities is to improve recognition accuracy. Combining two or more biometric technologies with other factors, such as different biometric patterns may be more suitable for unique deployment scenarios, or security is crucial for protecting sensitive data.
In many application fields, the financial industry has a huge demand for multimodal recognition. Overall, multimodal biometric technology can help reduce the losses caused by financial fraud, ensure the security of user information and data, outperform single biometric technology, and may become a future trend in financial technology. However, with a total of 100000 bank branches nationwide, the entire planning and preparation work, including the construction of backend service systems and product form planning, requires a large amount of time to explore, experiment, and promote the implementation.
Nowadays, biometric identification is moving from singularity to multimodality, and a single biotechnology identification cannot support increasingly complex and diverse identity verification scenarios. However, multimodal biometric identification can combine multiple biometrics such as fingerprints, faces, iris, voiceprints, etc., to achieve more accurate identity authentication and centralized and unified system management. It is worth mentioning that deploying multi-modal biometric systems can address some limitations in single modal biometric systems. Integrate multiple biometric modes in a single scan to alleviate the pressure of a single modality system.
In people's daily lives, they are increasingly exposed to multimodal biometrics, such as social security, smart locks, and park access control management. The combination of vein and face authentication can improve the accuracy of authentication data. For example, applications such as subway turnstiles, personal identity authentication for the college entrance examination, and verification of social security and pension payments.
As the gateway to artificial intelligence, biometric recognition is a prerequisite for intelligent services. Especially in the context of the booming construction of "new infrastructure", the future market driving force will extend horizontally and vertically, making it a major trend for the development of artificial intelligence in the future, which is safer, more extensive, highly recognizable, and has a high customer experience. Multimodal fusion will inevitably become a major characteristic of AI development.
In summary, multimodal biometric recognition enriches scene data and makes recognition more accurate; On the other hand, it is more suitable for application changes in complex scenarios. At present, the mainstream human ID verification terminal systems in the market are mainly composed of three key parts: multimodal algorithms (including OCR, fingerprint, and facial recognition), intelligent hardware, and human ID verification software. The product forms include desktop, handheld, wall mounted, and channel based.
A multimodal unified authentication platform that integrates multiple recognition technologies will play an important role in the implementation and application of biometric technology. Based on decision weights and scenario requirements, the multimodal unified authentication platform can flexibly and automatically configure suitable biometric technologies, which is a better state of technological development. However, multimodal recognition still faces market challenges during its implementation, and industry enterprises need to work together to promote the commercialization and large-scale application of technology.
According to market research firm MarketsandMarkets, the biometric market is expected to grow rapidly from $16.8 billion in 2018 to $41.8 billion in 2023, with a compound annual growth rate of 19.99%. This vast market blue ocean still needs to be explored.
Software plays an important role in ensuring the compatibility and interoperability of biometric devices. For biometric devices, the adoption of cloud based services and AI is expected to increase the demand for related software to ensure compatibility between devices and operating systems for different applications. At the same time, users can integrate additional functions into existing hardware by updating software, and supplement hardware functions by storing and calling spatial data to achieve better results.
The commercial application of new technologies needs to prioritize standards. From the perspective of protecting user rights, maintaining industry stability, and ensuring stable and healthy economic development, developing practical, effective, clear and feasible regulatory standards will become an important "gateway" for the large-scale application of multimodal biometrics.
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