Dynamic Pixel Binning for Optical Fingerprint Recognition
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Solution Overview
Problem
Existing fingerprint recognition systems face challenges in accurately distinguishing fine features due to large pixel sizes in image sensors, which can vary with display panel structures, leading to increased costs and reduced reliability across different devices.
Innovation Solution
A method utilizing a pixel binning scheme that dynamically adjusts the binning size based on fingerprint frequency, allowing for efficient registration and recognition of fingerprints by combining small pixels to generate a desired pixel signal, thereby enhancing compatibility with display panels and reducing pixel influence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If large pixel size is used in the image sensor, then light sensitivity is improved, but fine feature distinction capability deteriorates
Solution Approach 1:
The image sensor is divided into multiple pixel regions with different pixel sizes. Specifically, first pixel regions with larger pixel sizes are used for capturing areas requiring higher light sensitivity, while second pixel regions with smaller pixel sizes are used for capturing areas requiring finer detail resolution. This segmentation allows each region to be optimized for its specific function, resolving the contradiction between light sensitivity and fine feature distinction.
2Measurement precision
If the fingerprint recognition system is redesigned for each display device, then recognition performance is improved, but manufacturing cost and complexity increase
Solution Approach 1:
The fingerprint recognition system is designed with a universal pixel binning scheme that can adapt to different display panel structures without requiring device-specific redesigns. The system uses configurable binning modes (e.g., 2x2, 4x4, or other patterns) that can be adjusted through software control to match various display characteristics. This multi-functionality allows a single hardware design to serve multiple device types while maintaining optimal recognition performance.
Solution Approach 2:
The pixel binning configuration is made dynamic and adjustable rather than fixed. The system can switch between different binning modes and patterns based on the specific display panel being used, allowing optimal adaptation to various display structures without physical redesign. This dynamic adaptability reduces manufacturing complexity while preserving recognition performance across different devices.
3Device complexity
If fixed pixel binning size is used, then system simplicity is improved, but adaptability to different fingerprint frequencies deteriorates
Solution Approach 1:
The pixel binning size is made dynamic and adjustable rather than fixed. The system supports multiple binning configurations (e.g., different binning modes and patterns) that can be selected and adjusted based on the detected fingerprint frequency characteristics. This allows the system to adapt to different users and fingerprint patterns while maintaining relatively simple hardware architecture, thus balancing system simplicity with adaptability.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach improves fingerprint recognition performance by optimizing pixel size for each device, increasing compatibility and reducing manufacturing defects, while allowing for seamless integration across various display structures without redesigning the fingerprint recognition system.
Implementation Method 1
Fingerprint recognition uses imaging sensors to recognize a user's fingerprint, based on differences in the light reflected off the ridges and valleys of a fingertip
Data Source
AI summary
Systems and methods are described for registering a fingerprint based on optical fingerprint recognition. A fingerprint recognition window is displayed and a fingerprint frequency of a user fingerprint is analyzed based on reflected light received through the fingerprint recognition window using a fingerprint recognition sensor driven by a pixel binning scheme based on a first binning size. The first binning size may be evaluated based on the fingerprint frequency. If the first binning size is not appropriate for registering the user fingerprint, a second binning size is selected. Fingerprint information of the user fingerprint may be obtained again based on using the fingerprint recognition sensor driven by a pixel binning scheme based on the second binning size.