Spoof Detection via Subject Motion Estimation from Image Frames
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Biometric authentication systems face challenges in differentiating between live individuals and spoof representations, such as photographs or masks, which can lead to unauthorized access, especially in resource-constrained environments like mobile devices.
Innovation Solution
The method involves capturing a sequence of images from varying relative positions between the image acquisition device and the subject, using sensor data to estimate the motion of the device and subtracting it from the total motion observed in the images to determine the subject's motion, thereby distinguishing between live persons and spoof representations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If biometric authentication systems use image capture devices to authenticate users, then authentication capability is provided, but the system cannot differentiate between live individuals and spoof representations leading to unauthorized access
Solution Approach 1:
The system performs liveness detection by analyzing motion characteristics in captured images before completing the authentication process. This preliminary action identifies spoof representations (photographs, masks) by detecting abnormal motion patterns, preventing unauthorized access before it can occur while maintaining a relatively simple device architecture
Solution Approach 2:
The patent replaces complex hardware-based liveness detection mechanisms with software-based motion analysis of captured images. By using image processing algorithms to analyze motion characteristics between sequential frames, the system achieves reliable spoof detection without adding complex mechanical or sensor hardware
2Measurement precision
If the system captures multiple images from varying relative positions to detect motion, then liveness detection accuracy is improved, but processing time and computational resources increase
Solution Approach 1:
The system captures a sequence of images during the natural authentication process and analyzes motion characteristics from these images. By using motion analysis on sequential frames already captured during positioning, the system achieves accurate liveness detection without requiring additional capture time or excessive computational resources beyond the basic authentication workflow
Data Source
AI summary
A method includes receiving a first image and a second image, wherein the first and second images represent first and second relative locations, respectively, of an image acquisition device with respect to a subject. The method also includes determining, using the first and second images, a total relative displacement of the subject with respect to the image acquisition device between a time of capture of the first image and a time of capture of the second image, and determining, based on sensor data associated with one or more sensors associated with the image acquisition device, a component of the total relative displacement associated with a motion of the image acquisition device. The method also includes determining, based on a difference between the first total relative displacement and the component, that the first subject is an alternative representation of a live person, and in response, preventing access to a secure system.