On-line Signature Verification Based on Modified Dynamic Time Warping and Wavelet Sub-band Coding

Abstract

This paper presents an on-line signature biometric system based on a modified Dynamic Time Warping (DTW) algorithm applied to the signature wavelet coefficients. The modification on DTW relies on the use of direct matching points information (DMP) to dynamically adapt the similarity measure during the matching process, which is shown to increase the verification success rate. The wavelet analysis is done using a sub-band coding algorithm at global and local level. The use of wavelet coefficients showed a considerable reduction in processing time and an improvement in the equal error recognition rate (EER). The system was tested using a locally constructed database. A comparison of the ROC curves obtained in each case is presented.

Analysis of the Effects and Relationship of Perceived Handwritten Signature's Size, Graphical Complexity, and Legibility with Dynamic Parameters for Forged and Genuine Samples

“…With the advancement of current technologies, signature images can also be captured through the online mechanism. The online system often involves the use of digitizing tablets and pens which are used to capture the dynamic signing information (5,(8)(9)(10)(11)(12)(13)(14)(15). Signature dynamics can be processed further to provide features such as the signing velocity, acceleration, pen pressure, and strokes along the signing trajectory.…”

“…The majority of other relevant literatures on signature dynamics are found in the biometric domain which often makes use of black‐box machine learning algorithms such as Hidden Markov Model and support vector machine , where the knowledge remains hidden within system parameters. There are other types of signature biometrics which verify identities based on similarity score or distance measures such as Principle Component Analysis and Dynamic Time Warping . However, the separation rules have rarely been extracted and published for forensic knowledge consumption.…”