Optical Fingerprint Sensor Layout for Anti-Counterfeiting Authentication
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Solution Overview
Problem
Conventional optical fingerprint sensors are susceptible to counterfeiting due to their inability to sense color images and lack of special positioning codes or patterns, which compromises the security of fingerprint recognition systems in consumer and portable electronic devices.
Innovation Solution
Incorporating positioning pixels and color pixels into the pixel array of optical fingerprint sensors to add fingerprint positioning codes and skin tone codes, respectively, which convert direct recordings of minutia points into vectors representing relative locations, making it difficult to rebuild a fingerprint image even if the minutia map is hacked or leaked.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional optical fingerprint sensors use only grayscale pixels without positioning codes, then the device complexity is low and manufacturing is simple, but the anti-counterfeiting capability and security are insufficient
Solution Approach 1:
The pixel array is segmented into three distinct types of pixels: grayscale pixels for capturing fingerprint ridge-valley patterns, color pixels for detecting skin tone information, and positioning pixels for providing reference coordinates. This segmentation allows each pixel type to perform its specific function optimally while collectively enhancing security without requiring complete redesign of the entire sensor system.
Solution Approach 2:
The patent merges multiple functionality into a single pixel array structure: grayscale imaging capability, color detection capability, and positioning code generation are all integrated into one sensor array. This combining approach achieves enhanced anti-counterfeiting capability without requiring separate sensors for each function, thus limiting the increase in device complexity.
2Reliability
If color pixels are added to detect skin tone information, then the anti-counterfeiting capability is enhanced, but the device complexity and manufacturing difficulty increase
Solution Approach 1:
Color pixels are not distributed uniformly across the entire pixel array but are strategically placed at specific locations where skin tone information is most valuable for authentication. This local quality approach allows the system to gain color-based security benefits while minimizing the number of color pixels required, thereby reducing manufacturing complexity compared to a full-color sensor array.
3Reliability
If positioning pixels are incorporated to generate positioning codes, then the difficulty of counterfeiting increases, but the device complexity and processing requirements increase
Solution Approach 1:
Positioning pixels are pre-configured in fixed patterns within the pixel array before fingerprint capture begins. These positioning pixels continuously provide reference coordinate information that is preliminarily processed and integrated with the grayscale and color pixel data. This preliminary action simplifies the overall processing required during authentication, as the positioning framework is already established and does not require complex real-time computation.
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
Enhances the anti-counterfeiting capability of fingerprint recognition systems by adding an additional layer of security through vector comparison instead of direct minutia point comparison, ensuring secure authentication in electronic devices.
Implementation Method 1
an array of photodiodes arranged in rows and columns within the semiconductor substrate and configured to accumulate charge from photons incident on the photodiodes
Data Source
AI summary
A method of fingerprint verification includes capturing a fingerprint image by an image sensing device. The image sensing device including a pixel array of a combination of sensing pixels configured to capture minutia points in the fingerprint image and positioning pixels configured to provide positioning codes. The method further includes calculating vectors of the minutia points with reference to the positioning codes, comparing the vectors to reference vectors generated from a reference fingerprint image, and determining a match between the fingerprint image and the reference fingerprint image based on the comparing of the vectors.