Compressed sensing approach for wrist vein biometrics

Area of Science:

• Biometrics and Security
• Optical Engineering
• Signal Processing

Background:

• Wearable biometric systems face challenges with size and complexity.
• Traditional vein recognition often requires bulky optical components.
• Compressed sensing (CS) offers a potential solution for miniaturization.

Purpose of the Study:

• To develop a compact wearable system for wrist vein recognition.
• To explore the application of compressed sensing (CS) with single-pixel detection for biometrics.
• To evaluate different spatial light modulation (SLM) techniques for practical implementation.

Main Methods:

• Utilized compressed sensing (CS) with single-pixel detection.
• Implemented spatial light modulation (SLM) using a liquid crystal display and a diffusely scattering medium.
• Analyzed the trade-offs between different SLM methods for wearable applications.
• Proposed a solution for misalignment issues in imaging systems.

Main Results:

• Demonstrated that CS with SLM can eliminate the need for complex optical systems in wearable devices.
• Compared the practical implementation aspects of two distinct SLM approaches.
• Addressed and proposed a solution for common misalignment problems in photodiodes-based imaging.

Conclusions:

• The proposed CS-based wearable system offers a promising, compact solution for wrist vein recognition.
• The choice of SLM technique impacts the practical feasibility of the CS approach.
• The system design advances the development of unobtrusive and effective biometric authentication devices.