Fingerprint Medium Consistency Detection for Novel Materials

The patent transforms the recognition approach from using static statistical features to using dynamic physical parameters (acoustic impedance, surface distance) derived from ultrasonic echo signals. This parameter transformation enables accurate classification of both extreme populations and novel materials by capturing real-time physical characteristics rather than relying on predetermined statistical distributions.

The patent performs preliminary offline collection and analysis of physical features from real fingers to establish reference data. This preliminary action creates a baseline of acoustic impedance and surface distance characteristics that are then used for real-time verification, improving accuracy without increasing online recognition complexity.

The patent replaces static classification thresholds with dynamic physical parameter measurements. Instead of fixed threshold intervals based on collected statistics, the system continuously measures acoustic impedance and surface distance in real-time, adapting to different finger conditions and material properties. This dynamic approach maintains reliability across diverse populations and materials while keeping the implementation straightforward through direct physical measurement.

The patent substitutes the statistical analysis system with a physics-based measurement system using ultrasonic waves. By replacing complex statistical feature analysis with direct measurement of acoustic impedance and surface distance, the system achieves higher reliability without sacrificing implementation ease, as the physical measurements provide direct, objective criteria for classification.

The patent replaces static statistical distribution laws with dynamic physical parameter measurements that adapt in real-time to different materials. By measuring acoustic impedance and surface distance directly during verification, the system maintains fast processing speed while achieving high adaptability to novel medium materials, as the physical measurements naturally accommodate different material properties without requiring retraining or threshold adjustment.

The patent changes the basis of recognition from fixed statistical parameters to variable physical parameters. The acoustic impedance and surface distance measurements inherently adapt to different materials including novel medium materials, maintaining fast processing through direct measurement while achieving universal adaptability across diverse fingerprint sources without relying on pre-collected statistical distributions.