Deep neural networks have become prevalent in human analysis, boosting the performance
of applications, such as biometric recognition, action recognition, as well as person re …

A major limitation to advances in fingerprint presentation attack detection (PAD) is the lack of
publicly available, large-scale datasets, a problem which has been compounded by …

Synthetic biometric samples are created with an ultimate goal of getting around privacy
concerns, mitigating biases in biometric datasets, and reducing the sample acquisition effort …

Much of the success of fingerprint recognition is attributed to minutiae-based fingerprint
representation. It was believed that minutiae templates could not be inverted to obtain a high …

Billions of contact-based fingerprint images have been acquired in large databases.
Contactless 2D fingerprint identification systems have emerged to provide more hygienic …

Featured Application Getting around privacy concerns that arise when evaluating biometric
systems with real biometric samples by introducing privacy-friendly datasets of synthetic …

Fingerprint reconstruction from minutiae performed by model-based approaches often lead
to fingerprint patterns that lack realism. In contrast, data-driven reconstruction leads to …

Fingerprint recognition has been a vital security guard for various applications whose
vulnerability has been explored by different works. However, previous works on spoofing …

Several attempts have been made recently to generate synthetic fingerprint data. This has
become necessary after legal changes in Europe and some US states in order to allow and …

Fingerprints are crucial in identification of humans. The uniqueness of finger prints makes it
an interesting subject. Fingerprints are termed as a technique used to define, assess, and …