Deep learning-based face anti-spoofing detection using an efficient dual-unit preprocessing model for secured biometrics

Key Points

• The main aim is to develop an efficient preprocessing model to enhance face anti-spoofing detection accuracy in biometric systems.
• Developed a dual-unit preprocessing model for image analysis.
• Applied deep learning techniques to improve facial recognition.
• Executed tests on various face spoofing attack scenarios.
• Achieved higher detection accuracy compared to traditional methods.
• Demonstrated reduced false acceptance rates in biometric systems.
• Improved processing speed for real-time applications.