Fingerprint Authentication Using Frequency-Based Template Prioritization

The system performs preliminary actions by learning and recording the using frequency of each fingerprint template in advance. Before actual authentication, the system has already prepared a sorted sequence of templates based on historical usage data, so that during authentication it can directly access the most frequently used templates first without needing to check all templates sequentially.

The matching sequence is made dynamic rather than static. The system continuously learns from user authentication patterns and adjusts the template matching sequence adaptively. Templates that are used more frequently are positioned higher in the matching sequence, and this sequence is updated over time based on changing usage patterns, optimizing authentication speed while maintaining reliability.

The system performs preliminary sorting of templates based on using frequency before authentication. By pre-processing the template list according to historical usage data, the system prepares an optimized matching sequence in advance, so that during actual authentication it can quickly access the most relevant templates without scanning through all registered templates.

The system automatically learns and adjusts the matching sequence without requiring manual intervention. It self-optimizes by monitoring authentication patterns and reordering templates based on observed usage frequency, thereby automatically adapting to user behavior while maintaining both comprehensive coverage and fast recognition speed.