The multimodal biometric fusion scheme has strong universality and mobility and is suitable for the fusion of data, features, scores and strategies. Based on the core biometric algorithm, the scheme builds core functions such as multi-modal data perception, multi-dimensional data deduction, intelligent feedback decision-making, data security sharing, AI engineering production, and provides service support for various business scenarios; adopts cloud native architecture to realize safe and convenient unified authentication and lightweight management.
Fingerprint and finger vein multimodal recognition algorithm can well solve the shortcomings of recognition using fingerprint or finger vein recognition singly, like incomplete imaging caused by fingerprint damage or unclear finger vein image caused by anemia.
The algorithm responds on millisecond level and the accuracy rate is above 99.5%.
The multi-modal algorithm of human iris face recognition fusion is imperceptible and has high accuracy. It can be applied to automatic collection machine to collect iris images with fast response and accuracy rate which is above 99.5%.
Suitable for applications in finance, parks, education, social security, coal mining and other industries.
Increase user-friendliness when ensure the accuray at the same time.
Palm vein liveness detection penetrates the vascular network through epidermal shedding interference. 3D palmprint modeling automatically compensates for hand dryness, oil stains or deformations. Dual-mode dynamic calibration achieves 99.99% success rate in extreme scenarios.
Palmprint and palm vein dual-modal liveness verification breaks through biometric limits. False acceptance rate drops to 0.0001% with near-zero false rejection rate.
Palm-based payment, access control and device unlocking with a single touch. Multi-modal liveness verification completed in 0.2 seconds. Operation time reduced by 80% compared to fingerprint recognition
