Contactless robust 3D palmprint identification using photometric stereo

Palmprints are of considerable interest as a reliable biometric, since they offer significant advantages, such as greater user acceptance than fingerprint or iris recognition. 2D systems can be spoofed by a photograph of a hand; however, 3D avoids this by recovering and analysing 3D textures and profiles. 3D palmprints can also be captured in a contactless manner, which is critical for ensuring hygiene (something that is particularly important in relation to pandemics such as COVID-19), and ease of use. Prior work includes low-resolution (relatively unreliable) 3D analysis of wrinkles, or higher resolution ridge analysis that usually employs a commercial (contact based) palmprint scanner. This gap between low and high-resolution palmprint recognition is bridged here using high-resolution non-contact photometric stereo. A camera and illuminants are synchronised with image capture to recover high-definition 3D texture data from the palm, which are then analysed to extract ridges and wrinkles. This novel low cost approach can tolerate distortions inherent to unconstrained contactless palmprint acquisition. Features are found using discrete Fourier transforms. After alignment to a global ridge pattern, feature correspondences are matched, enabling reliable non-contact palmprint identification. The system was evaluated on a medium-sized database and matching was achieved with 0.1% equal error rate, which shows that the approach can achieve accurate and user-friendly palmprint recognition.

Automated summary

Palmprints are a reliable biometric with high user acceptance, and 3D palmprint systems avoid spoofing by photos and can be captured in a contactless manner for hygiene and convenience. A novel approach using high-resolution non-contact photometric stereo is able to bridge the gap between low and high-resolution palmprint recognition, allowing for accurate and user-friendly palmprint identification.