Fingerprint Presentation Attack Detection Based on Local Features Encoding for Unknown Attacks
Lazaro J. Gonzalez-Soler,Marta Gomez-Barrero,Leonardo Chang,Airel Pérez-Suárez,Christoph Busch +4 more
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TLDR
In this paper, the authors proposed a new PAD technique based on three image representation approaches combining local and global information of the fingerprint, which can correctly discriminate bona fide from attack presentations in the aforementioned scenarios.Abstract:
Fingerprint-based biometric systems have experienced a large development in the past. In spite of many advantages, they are still vulnerable to attack presentations (APs). Therefore, the task of determining whether a sample stems from a live subject (i.e., bona fide) or from an artificial replica is a mandatory requirement which has recently received a considerable attention. Nowadays, when the materials for the fabrication of the Presentation Attack Instruments (PAIs) have been used to train the Presentation Attack Detection (PAD) methods, the PAIs can be successfully identified in most cases. However, current PAD methods still face difficulties detecting PAIs built from unknown materials and/or unknown recepies, or acquired using different capture devices. To tackle this issue, we propose a new PAD technique based on three image representation approaches combining local and global information of the fingerprint. By transforming these representations into a common feature space, we can correctly discriminate bona fide from attack presentations in the aforementioned scenarios. The experimental evaluation of our proposal over the LivDet 2011 to 2019 databases, yielded error rates outperforming the top state-of-the-art results by up to 72% in the most challenging scenarios. In addition, the best representation achieved the best results in the LivDet 2019 competition (overall accuracy of 96.17%).read more
Citations
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Journal ArticleDOI
Fingerprint Spoof Detector Generalization
Tarang Chugh,Anil K. Jain +1 more
TL;DR: A style-transfer based wrapper, called Universal Material Generator (UMG), is presented, to improve the generalization performance of any fingerprint spoof (presentation attack) detector against spoofs made from materials not seen during training.
Journal ArticleDOI
HyFiPAD: a hybrid approach for fingerprint presentation attack detection using local and adaptive image features
Deepika Sharma,Arvind Selwal +1 more
TL;DR: A new hybrid fingerprint presentation attack detection approach (HyFiPAD) that discriminates live and fake fingerprints using majority voting ensemble build on three local and adaptive textural image features is expound that demonstrates superiority against majority of the state-of-the-art methods.
Journal ArticleDOI
An intelligent approach for fingerprint presentation attack detection using ensemble learning with improved local image features
Deepika Sharma,Arvind Selwal +1 more
TL;DR: In this article, an intelligent fingerprint PAD (IFPAD) approach was proposed for securing typical Cyber Physical Systems (CPS) that exploits two micro-textural features from an image.
Proceedings ArticleDOI
Fingerprint Presentation Attack Detection: A Sensor and Material Agnostic Approach
TL;DR: Wang et al. as mentioned in this paper proposed a robust PAD solution with improved cross-material and cross-sensor generalization, which built on top of any CNN-based architecture trained for fingerprint spoof detection combined with crossmaterial spoof generalization using a style transfer network wrapper.
Journal ArticleDOI
FinPAD: State-of-the-art of fingerprint presentation attack detection mechanisms, taxonomy and future perspectives
Deepika Sharma,Arvind Selwal +1 more
TL;DR: A comprehensive survey of fingerprint presentation attack detection can be found in this article, where the authors expound state-of-the-art fingerprint PAD mechanisms along with taxonomy covering the period of 2001 to 2021.
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