K-nearest neighbour and dynamic time warping for online signature verification
This work addresses biometric security for office and mobile scenarios, but it is incremental as it applies existing methods to a new database.
The paper tackled online signature verification by combining k-nearest neighbor and dynamic time warping algorithms, achieving error rates of 6.04% for stylus input, 5.20% for finger input, and 6.00% for combined types on a development set.
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 k-nearest 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.