In the recent past, deep learning methods have demonstrated remarkable success for
supervised learning tasks in multiple domains including computer vision, natural language …

Biometric systems are playing a key role in the multitude of applications and placed at the
center of debate in the scientific research community. Among the numerous biometric …

The active modality of handwriting is broadly related to signature verification in the context of
biometric user authentication systems. Signature verification aims to verify a questioned …

Nowadays, the verification of handwritten signatures has become an effective research field
in computer vision as well as machine learning. Signature verification is naturally formulated …

In this letter, we propose a vein-based biometric verification system relying on deep
learning. A novel approach consisting of a convolutional neural network (CNN), trained in a …

In-air signature verification is vital for biometric user identification in contact-less mode. The
state-of-the-art methods use heuristics for signature acquisition, and provide insufficient data …

On-line handwritten signatures are collected as real-time dynamical signals, which are
written on collective devices by users. Since writing environments are always changed …

In-air signature is a new modality which is essential for user authentication and access
control in noncontact mode and has been actively studied in recent years. However, it has …

At present, the common online signature verification systems adopt the contacted model of
signing on a tablet or a phone screen, which have a great dependence on the device …

This paper proposes a dynamic verification scheme for finger-drawn signatures in
smartphones. As a dynamic feature, the movement of a smartphone is recorded with …