Fingerprint biometric liveness software entries invited for LivDet 2025 round 2

Registration is about to open for round two of LivDet 2025, the prominent global competition for fingerprint biometric systems secured with Presentation Attack Detection (PAD).
The 2025 edition, the ninth running of the Fingerprint Liveness Detection Competition (LivDet), includes both contact and contactless fingerprint systems in recognition of the recent evolution of biometric technology. The organizers encourage the submission of innovative systems that bridge traditional contact-based systems and emerging contactless approaches, to support advances in fingerprint sensors and smartphone-based systems alike.
The second round of LivDet 2025 involves three challenges. The first, “Liveness Detection in Action,” requires the submission of an algorithm that generates an “integrated score” based on both the likelihood of a match and a bona fide sample. The second, “Fingerprint Representation,” requires PAD systems to return a feature embedding for the input image of 512 bytes or less. The third, “Adversarial Recognition,” asks competitors to provide a PAD solution that detects even adversarial presentation attacks.
All participants are evaluated for the third challenge, but can chose to compete in either or both of the first two, the same is in the first round.
Algorithms were submitted for round one of LivDet 2025 last year.
The competition is run by the Department of Electrical and Electronic Engineering of the University of Cagliari, the da/sec Group of the Hochschule Darmstadt, and the Department of Electrical and Computer Engineering of Clarkson University.
Registration for round two open on February 1, 2025, and closes April 1. Algorithm submissions for entries must be made by April 20.
Tech5 reported high marks in the contactless system portion of the previous running of the competition, LivDet 2023.
Article Topics
biometric liveness detection | biometric testing | biometrics research | fingerprint biometrics | LivDet | presentation attack detection
Comments