Biometric Sensor Artifact Compensation for Authentication Accuracy
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Solution Overview
Problem
Biometric sensors, such as fingerprint sensors, can develop fixed-location artifacts like scratches or non-operational pixels over time, which affect the false acceptance and false rejection rates, leading to inaccurate user authentication.
Innovation Solution
A method is provided to detect and manage these artifacts by analyzing a series of images from the sensor, identifying specific pixel locations with consistent biases, and compensating for the artifact patterns in subsequent images, thereby reducing the impact of scratches and non-operational pixels on authentication accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If biometric sensors are used for authentication, then user identification can be performed, but sensor artifacts like scratches and non-operational pixels cause false acceptance and false rejection rates to increase
Solution Approach 1:
The system performs preliminary actions by capturing multiple images of the same biometric object and analyzing them to identify artifact patterns before authentication occurs. By detecting consistent pixel value biases across multiple images, the system pre-identifies sensor artifacts and creates compensation data that will be applied during subsequent authentication attempts, thereby preventing false acceptance and rejection errors.
Solution Approach 2:
The system implements feedback by continuously monitoring sensor output, comparing pixel values across multiple images, and using the analyzed artifact patterns to adjust future authentication decisions. The feedback loop involves: capturing images, analyzing for artifacts, identifying consistent biases, and applying compensation to subsequent authentication processes, thereby continuously improving reliability based on observed sensor behavior.
2Reliability
If multiple images are analyzed to detect artifact patterns, then authentication reliability improves, but processing time and computational complexity increase
Solution Approach 1:
The system segments the image analysis process by focusing on specific pixel locations that show consistent biases across multiple images, rather than processing every pixel in detail. By identifying artifact patterns at specific locations and creating targeted compensation data for those areas, the system reduces the overall computational burden while maintaining high reliability in authentication decisions.
Solution Approach 2:
The system changes parameters by transforming raw pixel values into normalized or compensated values based on identified artifact patterns. Instead of processing all original images with their artifact-contaminated data, the system adjusts the parameter space by applying correction factors derived from artifact analysis, thereby reducing processing time while maintaining authentication accuracy.
3Reliability
If artifact compensation is applied to sensor data, then false acceptance and false rejection rates decrease, but device complexity increases due to additional processing steps
Solution Approach 1:
The system creates a copy or representation of the artifact pattern data and uses this copied information to compensate for sensor defects during authentication. Instead of physically modifying the sensor or using complex hardware corrections, the system generates a data model of the artifacts and applies this model through software processing, thereby managing complexity through information replication rather than physical modification.
Solution Approach 2:
The system discards or masks the corrupted pixel data corresponding to artifact locations and recovers the authentication decision by using compensated values derived from the artifact pattern analysis. By separating the corrupted data from the analysis process and replacing it with corrected values, the system manages complexity through selective data handling rather than attempting to correct every defect physically.
Data Source
AI summary
Systems and methods for identifying and managing fixed sensor artifacts, such as scratches and non-operational sensor pixels, in a biometric sensor. A plurality of images acquired by the biometric sensor in response to detection of a biometric object proximal to a sensing surface of the biometric sensor are processed to determine a pixel value for each pixel location in each image. One or more specific pixel locations having substantially the same pixel value in the plurality of images are identified an artifact pattern of the biometric sensor.