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.

scholarly journals Preprocessing approaches in DTW based online signature verification

2020 ◽  
Vol 15 (1) ◽  
pp. 148-157
Author(s):  
Mohammad Saleem ◽  
Bence Kovari
Keyword(s):  
Dynamic Time Warping ◽  
Signature Verification ◽  
Vertical Scaling ◽  
Time Warping ◽  
Online Signature ◽  
Different Dimensions ◽  
Online Signature Verification ◽  
Dynamic Time

Abstract Amongst different approaches, dynamic time warping has shown promising results during the online signature verification competitions of previous years. To improve the results of dynamic time warping, different preprocessing steps may be applied and different dimensions of the samples may be compared. The choice of preprocessing steps and comparing dimensions may significantly influence the results. Thus, to aid researchers with these decisions, a comparison made between the results of promising preprocessing algorithms as horizontal scaling, vertical scaling and alignment using dynamic time warping in different dimensions and their combinations on two datasets (SVC2004 and MCYT-100). The results showed that preprocessing methods made a very promising improvement in the verification accuracy.

scholarly journals Online signature verification using signature down-sampling and signer-dependent sampling frequency

2021 ◽  
Author(s):  
Mohammad Saleem ◽  
Bence Kovari
Keyword(s):  
Sampling Rate ◽  
Sampling Frequency ◽  
Signature Verification ◽  
Point Count ◽  
Digital Devices ◽  
Verification System ◽  
Verification Methods ◽  
Online Signature ◽  
Online Signature Verification ◽  
Verification Systems

AbstractOnline signature verification considers signatures as time sequences of different measurements of the signing instrument. These signals are captured on digital devices and therefore consist of a discrete number of samples. To enrich or simplify this information, several verifiers employ resampling and interpolation as a preprocessing step to improve their results; however, their design decisions may be difficult to generalize. This study investigates the direct effect of the sampling rate of the input signals on the accuracy of online signature verification systems without using interpolation techniques and proposes a novel online signature verification system based on a signer-dependent sampling frequency. Twenty verifier configurations were created for five different public signature databases and a variety of popular preprocessing approaches and evaluated for 20–40 different sampling rates. Our results show that there is an optimal range for the sampling frequency and the number of sample points that minimizes the error rate of a verifier. A sampling frequency range of 15–50 Hz and a signature point count of 60–240 provided the best accuracies in our experiments. As expected, lower ranges showed inaccurate results; interestingly, however, higher frequencies often decreased the verification accuracy. The results show that one can achieve better or at least the same verification accuracies faster by down-sampling the online signatures before further processing. The proposed system achieved competitive results to state-of-the-art systems for different databases by using the optimal sampling frequency. We also studied the effect of choosing individual sampling frequencies for each signer and proposed a signature verification system based on signer-dependent sampling frequency. The proposed system was tested using 500 different verification methods and improved the accuracy in 92% of the test cases compared to the usage of the original frequency.

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