A perspective analysis of handwritten signature technology
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 …
community. Over the last 40 years, the interest in signature studies has grown steadily …
Automated bank cheque verification using image processing and deep learning methods
Automated bank cheque verification using image processing is an attempt to complement
the present cheque truncation system, as well as to provide an alternate methodology for the …
the present cheque truncation system, as well as to provide an alternate methodology for the …
A survey of handwriting synthesis from 2019 to 2024: A comprehensive review
Handwriting, as a uniquely human skill, contributes to fine motor development and cognitive
growth. Beyond mere functionality, handwriting carries individuality and subtle emotional …
growth. Beyond mere functionality, handwriting carries individuality and subtle emotional …
Writer independent handwritten signature verification on multi-scripted signatures using hybrid CNN-BiLSTM: A novel approach
T Longjam, DR Kisku, P Gupta - Expert Systems with Applications, 2023 - Elsevier
Authenticating important documents by identifying individuals using handwritten signatures
make signature verification a critical task. Interpersonal similarity and intrapersonal variation …
make signature verification a critical task. Interpersonal similarity and intrapersonal variation …
Fixed-sized representation learning from offline handwritten signatures of different sizes
Methods for learning feature representations for offline handwritten signature verification
have been successfully proposed in recent literature, using deep convolutional neural …
have been successfully proposed in recent literature, using deep convolutional neural …
SynSig2Vec: Forgery-free learning of dynamic signature representations by sigma lognormal-based synthesis and 1D CNN
Handwritten signature verification is a challenging task because signatures of a writer may
be skillfully imitated by a forger. As skilled forgeries are generally difficult to acquire for …
be skillfully imitated by a forger. As skilled forgeries are generally difficult to acquire for …
Forgery-free signature verification with stroke-aware cycle-consistent generative adversarial network
In recent years, the performance of handwritten signature verification (HSV) has been
considerably improved by deep learning methods. However, deep HSV still faces significant …
considerably improved by deep learning methods. However, deep HSV still faces significant …
iDeLog: iterative dual spatial and kinematic extraction of sigma-lognormal parameters
The Kinematic Theory of rapid movements and its associated Sigma-Lognormal model have
been extensively used in a large variety of applications. While the physical and biological …
been extensively used in a large variety of applications. While the physical and biological …
Intrapersonal parameter optimization for offline handwritten signature augmentation
Usually, in a real-world scenario, few signature samples are available to train an automatic
signature verification system (ASVS). However, such systems do indeed need a lot of …
signature verification system (ASVS). However, such systems do indeed need a lot of …
Convolutional auto-encoder based deep feature learning for finger-vein verification
B Hou, R Yan - 2018 IEEE international symposium on medical …, 2018 - ieeexplore.ieee.org
This paper presents a novel deep learning-based method that integrates a Convolutional
Auto-Encoder (CAE) with Convolutional Neural Network (CNN) for finger vein verification …
Auto-Encoder (CAE) with Convolutional Neural Network (CNN) for finger vein verification …