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Current fingerprint anti-spoofing and liveness detection techniques heavily relied on image processing algorithms and did not fully explore other hardware of a smartphone. In this study, we utilize the phone’s front-facing teardrop notch camera and LED display for multi-spectral imaging and liveness detection. We programmed the phone to illuminate different RGB colors patterns while the camera captures images of the illuminated finger. A custom-designed software allows for the distinct detection between spoof and live fingers based on resulting images and video. The method was implemented and tested in a Samsung Galaxy A50 with a teardrop notch camera. Utilizing a MATLAB program, we were able to distinguish a real finger from eight different-colored spoofs based on the images captured from the front-facing camera.
Kaylin McQuillan,Wenhan Zheng, andJun Xia
"Multispectral anti-spoofing and liveness detection based on the front-view camera and the screen of a smartphone", Proc. SPIE 11632, Optics and Biophotonics in Low-Resource Settings VII, 116320A (5 March 2021); https://doi.org/10.1117/12.2578803
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Kaylin McQuillan, Wenhan Zheng, Jun Xia, "Multispectral anti-spoofing and liveness detection based on the front-view camera and the screen of a smartphone," Proc. SPIE 11632, Optics and Biophotonics in Low-Resource Settings VII, 116320A (5 March 2021); https://doi.org/10.1117/12.2578803