A new online signature verification system based on combining Mellin transform, MFCC and neural network

2011 ◽  
Vol 21 (2) ◽  
pp. 404-416 ◽  
Author(s):  
Asghar Fallah ◽  
Mahdi Jamaati ◽  
Ali Soleamani
Author(s):  
Vahab Iranmanesh ◽  
Sharifah Mumtazah Syed Ahmad ◽  
Wan Azizun Wan Adnan ◽  
Fahad Layth Malallah ◽  
Salman Yussof

2021 ◽  
Author(s):  
Mohammad Saleem ◽  
BenceKovari

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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