Fingerprint Sensor Non-Finger Object Rejection via Spatial Frequency Analysis
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Solution Overview
Problem
Capacitance-based fingerprint sensors face challenges in distinguishing real fingers from non-finger objects, leading to unnecessary power consumption and user interruptions due to false triggers by objects like coins or keys.
Innovation Solution
A fingerprint sensing system that employs spatial frequency analysis and ridge flow analysis to differentiate between real fingers and non-finger objects by scanning the sensor surface, filtering spatial frequencies within a predetermined range for human fingers, and analyzing ridge directions to determine the presence of a real finger.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If capacitance sensing is used for fingerprint detection, then the sensor can be placed in various locations on the device surface, but the sensor cannot distinguish between real fingers and non-finger objects, leading to false triggers
Solution Approach 1:
The patent segments the detection process into multiple stages: initial capacitance-based object detection, followed by spatial frequency analysis of the detected object's surface characteristics. This multi-stage segmentation allows the system to first identify any touching object using simple capacitance sensing, then apply more complex analysis only when needed to distinguish fingers from non-finger objects, thereby maintaining both versatility and reliability
Solution Approach 2:
The patent applies preliminary spatial frequency analysis to detect objects before initiating full fingerprint imaging and processing. By performing this preliminary check, the system can reject non-finger objects early in the detection sequence, preventing unnecessary activation of the host device and avoiding false triggers while preserving the ability to detect fingers accurately
2Productivity
If the sensor activates the host device for every detected object, then all objects including non-fingers are processed, but this causes unnecessary power consumption and user interruptions
Solution Approach 1:
The patent implements partial action by applying spatial frequency analysis selectively rather than to all detected objects. The system performs this additional analysis only on objects that require differentiation from fingers, based on initial capacitance characteristics. This partial application of the detection algorithm reduces unnecessary processing and power consumption while maintaining accurate detection response for genuine finger inputs
Solution Approach 2:
The patent introduces spatial frequency analysis as an intermediary step between simple object detection and full fingerprint processing. This intermediary mechanism acts as a filter that determines whether detected objects warrant further processing, thereby reducing the number of times the host device needs to be fully activated and reducing overall power consumption while maintaining detection responsiveness
3Reliability
If spatial frequency analysis is applied to all detected objects, then non-finger objects can be rejected, but this increases processing time and system complexity
Solution Approach 1:
The patent applies local quality by using different detection methods for different types of objects. Simple capacitance sensing is used for initial object detection, while spatial frequency analysis is applied locally only to objects that require differentiation from fingers. This localized application of complex analysis reduces overall system complexity while maintaining high reliability for non-finger object rejection where needed
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 reduces power consumption by maintaining the host device in a low power state until a real finger is detected, avoiding unnecessary image acquisition and processing of non-finger objects, thus enhancing the system's accuracy and efficiency.
Implementation Method 1
Capacitance-based fingerprint sensors function by measuring the capacitance of a capacitive sense element, such as a sensor electrode, and detecting a change in capacitance indicating a presence or absence of a fingerprint ridge (or valley)
Data Source
AI summary
A method for detecting a finger at a fingerprint sensor includes detecting a presence of an object at a fingerprint sensor and, in response to detecting the presence of the object, acquiring image data for the object based on signals from the fingerprint sensor. The method further includes, for each subset of one or more subsets of the image data, calculating a magnitude value for a spatial frequency of the subset, and identifying the object as a finger based on comparing the magnitude value to a threshold.