Fingerprint Sensor Superimposition for Dynamic Range
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Solution Overview
Problem
Common fingerprint sensing devices struggle to capture detailed fingerprint images due to varying brightness conditions and incomplete finger contact, leading to poor image quality in high-brightness and low-brightness regions.
Innovation Solution
A fingerprint sensing device and method that acquires multiple reference frames with different exposure times, analyzes them to determine distinct regions, and calculates pixel values using weight functions to generate a superimposed frame with improved clarity and dynamic range, ensuring precise fingerprint details.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a common fingerprint sensing method is used, then the sensing process is simple, but the image dynamic range is low and fingerprint details cannot be identified in high-brightness or low-brightness regions
Solution Approach 1:
The fingerprint sensing image is divided into multiple regions (high-brightness regions and low-brightness regions) based on brightness distribution. Different weight value functions are applied to different regions to optimize fingerprint detail identification in each region independently, resolving the contradiction between measurement precision and device complexity.
Solution Approach 2:
Different weight value functions are assigned to different regions of the fingerprint image based on their brightness characteristics. High-brightness regions receive one type of weight function while low-brightness regions receive another, allowing each region to be processed with optimal parameters for its specific conditions, thereby improving overall measurement precision without requiring complete system redesign.
2Measurement precision
If multiple fingerprint reference frames are acquired and superimposed with different weight value functions, then fingerprint image quality and dynamic range are improved, but the processing time and computational complexity increase
Solution Approach 1:
Multiple fingerprint reference frames are acquired in advance with different exposure times before the actual sensing operation. This preliminary acquisition allows the system to have pre-processed reference data ready, reducing the processing time during actual fingerprint sensing while maintaining high image quality through the superimposition of these pre-acquired frames.
Data Source
AI summary
A fingerprint sensing device includes a fingerprint sensor and a processor. The fingerprint sensor is configured to acquire a plurality of fingerprint reference frames. The processor is coupled to the fingerprint sensor. The processor is configured to superimpose the plurality of fingerprint reference frames. The processor analyzes the plurality of fingerprint reference frames to determine multiple first regions and multiple second regions of the plurality of fingerprint reference frames. The processor calculates multiple reference pixel values of the plurality of fingerprint reference frames according to multiple weight value functions to generate a superimposed fingerprint frame. The weight value functions corresponding to the first regions of the plurality of fingerprint reference frames are linearly changed.