Online signature verification system with anti-forgery provision based on segmentation and structure learning of HMM

2010 ◽  
Author(s):  
Dapeng Zhang ◽  
Shinkichi Inagaki ◽  
Naoki Kanada ◽  
Tatsuya Suzuki
Keyword(s):  
Structure Learning ◽  
Signature Verification ◽  
Verification System ◽  
Online Signature ◽  
Online Signature Verification

scholarly journals K-Nearest Neighbour and Dynamic Time Warping for Online Signature Verification

2021 ◽  
Author(s):  
Mohammad Saleem ◽  
BenceKovari
Keyword(s):  
Error Rate ◽  
Dynamic Time Warping ◽  
Signature Verification ◽  
Nearest Neighbour ◽  
Time Warping ◽  
Verification System ◽  
Online Signature ◽  
Online Signature Verification ◽  
Dynamic Time ◽  
Verification Systems

Online signatures are one of the most commonly used biometrics. Several verification systems and public databases were presented in this field. This paper presents a combination of knearest neighbor and dynamic time warping algorithms as a verification system using the recently published DeepSignDB database. Our algorithm was applied on both finger and stylus input signatures which represent both office and mobile scenarios. The system was first tested on the development set of the database. It achieved an error rate of 6.04% for the stylus input signatures, 5.20% for the finger input signatures, and 6.00% for a combination of both types. The system was also applied to the evaluation set of the database and achieved very promising results, especially for finger input signatures.

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