Depth-Based Liveness Verification Against 2D Spoof Images
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Solution Overview
Problem
Existing liveness verification systems are vulnerable to fraudsters using counterfeit images, as they cannot differentiate between a live subject and a two-dimensional representation, such as a printed document or screen image.
Innovation Solution
Employing cameras capable of capturing depth information to distinguish between a live subject and a non-live subject by analyzing the depth data of the captured image, comparing it with preconfigured values or thresholds, and verifying the alignment of pixel and depth edges.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional image capture methods are used, then the system is simple and easy to operate, but it cannot differentiate between live subjects and counterfeit images
Solution Approach 1:
The patent transitions from two-dimensional image capture to three-dimensional depth information capture. By enabling the camera to capture depth data alongside traditional images, the system gains the ability to distinguish between live three-dimensional subjects and two-dimensional counterfeit images, thereby improving liveness verification accuracy without requiring entirely new hardware
2Reliability
If depth information capture is added, then liveness verification capability is improved, but device complexity increases
Solution Approach 1:
The patent makes the camera system multi-functional by enabling it to capture both traditional two-dimensional images and three-dimensional depth information. This universal capability allows a single camera system to perform multiple verification functions (image quality assessment, liveness detection, depth-based authentication) without requiring separate specialized devices for each function
3Reliability
If depth data analysis is performed, then authentication security is enhanced, but processing time increases
Solution Approach 1:
The patent segments the verification process into distinct stages: capturing depth information, analyzing depth data to detect liveness, and comparing results against predefined thresholds. This segmentation allows each component to be optimized independently and enables parallel processing of depth analysis and image processing, reducing overall verification time while maintaining enhanced security
Data Source
AI summary
A method for determining authenticity of an object in real-time is disclosed. The method being performed by a processor includes receiving image data of the object. The image data includes both the captured image showing a visual representation of the object as well as depth data describing the relative distance between different objects in the image and the camera. This depth information is analyzed in order to determine a liveness of the object. The analysis may include verifying a sufficient change in depth between the subject and a background as well as comparing an edge of a foreground object to an expected edge or an edge determined from the image. Based on this analysis, a determination can be made as to whether the image is of a live (e.g., real) subject.