The fingerprint chip ID809, with its enhanced processing capabilities, fully optimized resource allocation and power efficiency, low cost, and flexible and easy-to-use advantages, can provide a secure, high-speed, and cost-effective hardware development platform for fingerprint recognition systems. Adopting a 150MHz high-performance ARM Cortex-M4 core, it provides a complete DSP instruction set and dedicated floating point unit (FPU), which can directly support complex operations such as trigonometric functions, filtering, and convolution to accelerate the execution speed of fingerprint algorithms. The kernel accesses flash memory at high speed with zero waiting, and the working performance at high frequency can reach 210DMIPS. The CoreMark test score can reach 565 points. Thus, with enhanced power, it supports the entire process of advanced fingerprint recognition operations, including fingerprint image preprocessing, segmentation and stitching, data feature extraction, feature matching, cross comparison, recognition unlocking, and a series of instructions, which can significantly improve the efficiency of fingerprint registration and matching. The chip is equipped with 1MB of large capacity built-in Flash and up to 128KB of SRAM, which can support the resource overhead of multiple fingerprint information storage and dynamic memory allocation during the recognition process.
The fingerprint chip ID809 is embedded with IDFinger V6.0 fingerprint algorithm. Eddie Ward has 16 years of profound accumulation in the field of fingerprints, and the IDFinger fingerprint algorithm is constantly iterating to improve performance based on market demand and user feedback. The all-new IDFinger V6.0 fingerprint algorithm has stable, accurate, fast, and reliable performance characteristics, as well as deep self-learning, adaptive, and 360 degree; Easy to use advantages such as arbitrary angle recognition enable accurate collection and recognition of various fingerprints, including rough, dry, and damaged fingerprints. Each fingerprint feature extraction and recognition can be quickly completed.