High-speed and Accurate Matching to 2 Billion Images in Seconds

We are able to achieve accurate search across 2 billion fingerprints in seconds with multi-scale image representation, high-speed heterogeneous matching framework and distributed parallel processing.

Heterogeneous Parallel Computing and Performance Optimization

Applying parallel computing algorithms using CUDA has significantly improved matching performance due to optimizations in areas such as memory access, local storage, code branches, instruction optimization, data transfers, etc.

Application of Persistent Memory in Image Search System

By applying the latest NVDIMM technology and memory mapping technology (mmap) in Linux, the system can store all image features necessary for heterogeneous parallel computing algorithms in a distributed memory database. This significantly lowers costs for massive image searches and enhances stability of the distributed image search system.

Contactless Fingerprint Acquisition and Privacy-Preserving Biometrics

By upgrading fingerprint acquisition technology to contactless 3D era, we provide secure, reliable and privacy-preserving biometrics technology to billions of people.

Technological Breakthroughs in Traditional Machine Learning Algorithms Revolutionize Fingerprint Recognition Technologies

Transforming the fingerprint matching problem into high-accuracy image search problem that surpasses the limitations of traditional machine learning in accuracy, training data and performance, truly a first for unlabeled matching.