Vascular Biometric Spoof Detection via Near-Infrared Vein Analysis
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Solution Overview
Problem
Existing biometric vein recognition systems face challenges in efficiently detecting and rejecting falsified presentations, often requiring significant computational resources and being vulnerable to malicious attempts, while also being resource-intensive.
Innovation Solution
A computational efficient method and device that uses 2D data processing for vascular biometric recognition, leveraging 3D analysis of subcutaneous veins to detect falsified presentations by analyzing patterns within images, particularly using near-infrared radiation to acquire subcutaneous vein images and comparing them to determine likelihood matches, which reduces computational complexity and effectively identifies genuine vein patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If 3D analysis of subcutaneous veins is performed to detect falsified presentations, then anti-spoofing capability is improved, but computational complexity increases
Solution Approach 1:
The patent segments the complex 3D analysis task into two distinct stages: (1) 2D image acquisition and preliminary processing, and (2) selective 3D analysis applied only to regions of interest or suspicious areas. This segmentation allows the system to maintain high anti-spoofing capability through 3D verification while significantly reducing overall computational complexity by avoiding full 3D analysis of entire images.
Solution Approach 2:
The patent applies partial 3D analysis only to specific regions or aspects of the vein patterns rather than performing exhaustive 3D analysis on all data. This partial action approach maintains sufficient anti-spoofing reliability by focusing computational resources on critical verification points while reducing overall computational burden.
2Measurement precision
If multiple images are acquired from different orientations to improve recognition accuracy, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The patent performs preliminary 2D image acquisition and analysis before committing to more time-consuming 3D analysis or additional multi-orientation acquisitions. This preliminary action allows the system to quickly filter out obviously fake presentations and only invest additional time in comprehensive multi-orientation acquisition when initially needed, thus balancing recognition accuracy with time efficiency.
Solution Approach 2:
The patent implements a dynamic acquisition strategy where the number and orientation of images acquired adapts based on initial analysis results. If 2D images provide sufficient confidence for genuine presentations, the system avoids time-consuming multi-orientation acquisitions. For suspicious cases, it dynamically increases acquisition complexity, thus optimizing the trade-off between measurement precision and time loss.
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
The solution provides robust and efficient recognition and identification of individuals, effectively detecting falsified presentations with reduced computational complexity, enhancing security against malicious attempts while being compatible with existing biometric systems and operable on limited resources.
Implementation Method 1
The veins images are provided by radiating the entity presented to the biometric vascular system by a first electromagnetic radiation being a near-infrared radiation
Data Source
AI summary
The invention concerns a method and a biometric acquisition device for biometric vascular recognition and/or identification. The method comprising a step of capturing a plurality of veins images (116, 117, 118) of supposed subcutaneous veins (21) of a same inspecting portion (20) of a presented entity (2) from various converging orientations (113, 114, 115). The method further comprises a step of determine if said entity is a spoof based on estimated likelihood that said supposed subcutaneous veins within said plurality of veins images (116, 117, 118) are likely projections of solid veins (120).