Off-line Chinese signature verification based on support vector machines

Authors:
Hairong Lv;Wenyuan Wang;Chong Wang;Qing Zhuo
Affiliations:
Department of Automation, Tsinghua University, Beijing 100084, China;Department of Automation, Tsinghua University, Beijing 100084, China;Department of Automation, Tsinghua University, Beijing 100084, China;Department of Automation, Tsinghua University, Beijing 100084, China
Venue:
Pattern Recognition Letters
Year:
2005

Citing 5
Cited 9

Wavelet-based off-line handwritten signature verification

Computer Vision and Image Understanding
A Tutorial on Support Vector Machines for Pattern Recognition

Data Mining and Knowledge Discovery
An off-line signature verification system using an extracted displacement function

Pattern Recognition Letters
An Off-Line Signature Verification System Using an Extracted Displacement Function

ICDAR '99 Proceedings of the Fifth International Conference on Document Analysis and Recognition
Off-line Signature Verification Using HMM for Random, Simple and Skilled Forgeries

ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition

A different approach to off-line handwritten signature verification using the optimal dynamic time warping algorithm

Digital Signal Processing
Offline Signature Verification Using Local Interest Points and Descriptors

CIARP '08 Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications
Off-line signature verification based on deformable grid partition and Hidden Markov models

ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Off-line signature verification based on grey level information using texture features

Pattern Recognition
Off-line signature verification systems: a survey

Proceedings of the International Conference & Workshop on Emerging Trends in Technology
Writer identification using directional ink-trace width measurements

Pattern Recognition
Deep learning networks for off-line handwritten signature recognition

CIARP'11 Proceedings of the 16th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Revision for recognizing Chinese handwritten sentences based on lexical, syntactical and corpus rules

ROCLING '11 ROCLING 2011 Poster Papers
A new approach to signature-based authentication

ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics

Quantified Score

Hi-index	0.10

Visualization

Abstract

This paper proposes a novel off-line Chinese signature verification method based on support vector machines. The method uses both static features and dynamic features. The static features include moment features and 16-direction distribution (an improvement on 4-direction distribution). The dynamic features include gray distribution and stroke width distribution. At last, support vector machine is used to classify the signatures. The main steps of constructing a signature verification system are discussed and experiments on real data sets show that the average error rate can reach 5%, which is obviously satisfactory. w that the average error rate can reach 5%, which is obviously satisfactory.