Handwritten signatures are biometric traits at the center of debate in the scientific
community. Over the last 40 years, the interest in signature studies has grown steadily …

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 …

The area of Handwritten Signature Verification has been broadly researched in the last
decades, but remains an open research problem. The objective of signature verification …

With the recent advancement in information technology field, the demand to develop a
person authentication system through verifying their offline signatures is gradually …

This paper presents a novel classification method, Deep Multitask Metric Learning (DMML),
for offline signature verification. Unlike existing methods that to verify questioned signatures …

Handwritten signatures are one of the most extensively utilized biometrics used for
authentication, and forgeries of this behavioral biometric are quite widespread. Biometric …

Handwritten signature verification is a widely used biometric for person identity
authentication in document forensics. Despite the tremendous efforts in past research, offline …

Automatic Offline Handwritten Signature Verification has been researched over the last few
decades from several perspectives, using insights from graphology, computer vision, signal …

In the study of image and vision computing, the generalization capability of an algorithm
often determines whether it is able to work well in complex scenes. The goal of this review …

Authenticating important documents by identifying individuals using handwritten signatures
make signature verification a critical task. Interpersonal similarity and intrapersonal variation …