Biometric Image Noise Reduction via Multi-Level Calibration

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Solution Overview

Problem

Biometric sensing devices often suffer from signal fixed pattern noise, which reduces their dynamic range and produces inaccurate biometric images due to noise that changes with signal level, affecting their reliability in identification and verification processes.

Innovation Solution

The use of at least two calibration images, each characterizing noise at different signal levels, to remove noise from biometric images captured by the device, either on a segment-by-segment or block-by-block basis, using interpolation or fitting functions such as least squares fitting.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If a single calibration image is used to characterize noise, then the calibration process is simple, but the noise characterization is inaccurate because noise changes with signal level

Engineering Contradiction:

Improvenoise characterization accuracyVSAvoidcalibration process complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The calibration process is segmented into multiple calibration images captured at different signal levels. Each calibration image characterizes noise at its specific signal level, and the biometric image is divided into segments that are processed using the appropriate calibration data. This segmentation approach improves noise characterization accuracy without requiring a single overly complex calibration model.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

Instead of using a single calibration image that attempts to cover all signal levels (excessive action), the patent uses multiple calibration images at specific signal levels (partial action). This partial calibration approach at key signal levels provides more accurate noise characterization than a single comprehensive calibration, while avoiding the complexity of continuous calibration across all possible signal levels.

Inventive Principle:

Principle #16Partial or excessive action

2Productivity

If noise is removed using a single calibration image, then the processing is fast, but the dynamic range is reduced due to inaccurate noise compensation

Engineering Contradiction:

Improvenoise removal speedVSAvoidbiometric image accuracy

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

Multiple calibration images are captured in advance at different signal levels during a calibration phase. These pre-captured calibration images store noise characteristics for various signal levels, allowing fast noise removal during biometric image processing by simply looking up and applying the appropriate calibration data without performing complex real-time calculations.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The calibration images serve as intermediary data structures that bridge the gap between the biometric sensing device and the noise removal process. These intermediaries pre-process and store noise characteristics, enabling efficient noise compensation during actual biometric image acquisition without requiring complex real-time analysis.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Measurement precision

If calibration images are captured at multiple signal levels, then noise characterization improves, but the calibration time increases

Engineering Contradiction:

Improvenoise characterization accuracyVSAvoidcalibration time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent applies partial calibration by capturing calibration images at a select number of representative signal levels rather than continuously across the entire dynamic range. This partial calibration at key signal levels provides sufficient noise characterization accuracy while significantly reducing the total calibration time compared to comprehensive multi-level calibration.

Inventive Principle:

Principle #16Partial or excessive action

4Device complexity

If noise removal is applied to the entire biometric image at once, then the processing is simple, but the precision is reduced due to signal level variations

Engineering Contradiction:

Improveprocessing complexityVSAvoidbiometric image accuracy

Core Design Contradiction:

Device complexityVSMeasurement precision

Solution Approach 1:

The biometric image is divided into multiple segments, where each segment is processed using noise removal techniques appropriate for its specific signal level. This segmentation allows each segment to be calibrated with higher precision using signal-level-specific calibration data, while the overall processing remains manageable through systematic segment-by-segment handling.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

Different noise removal approaches and calibration data are applied to different segments of the biometric image based on their local signal levels. Each segment receives tailored noise compensation suited to its specific characteristics, improving overall image accuracy while maintaining processing feasibility through localized rather than uniform processing.

Inventive Principle:

Principle #3Local quality

Data Source

PatentUS9552525B2Noise reduction in biometric images

Publication Date: 2017.01.24 APPLE INC

AI summary

A system can include a processing device and a biometric sensing device operatively connected to the processing device. The processing device can be configured to remove noise from a biometric image captured by the biometric sensing device using at least two different calibration images. One calibration image characterizes noise of the biometric sensing device at a first signal level while another calibration image characterizes the noise of the biometric sensing device at a second signal level.